├── LICENSE ├── MICCAI-2019.md ├── MICCAI-2020.md ├── MICCAI-2021.md ├── MICCAI-2022.md ├── README.md └── WordCloud ├── WordCloud-MICCAI2020.png ├── WordCloud-MICCAI2021.png ├── WordCloud-MICCAI2022.png └── WordCloud-MICCAI2023.png /LICENSE: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 6 | 7 | 1. Definitions. 8 | 9 | "License" shall mean the terms and conditions for use, reproduction, 10 | and distribution as defined by Sections 1 through 9 of this document. 11 | 12 | "Licensor" shall mean the copyright owner or entity authorized by 13 | the copyright owner that is granting the License. 14 | 15 | "Legal Entity" shall mean the union of the acting entity and all 16 | other entities that control, are controlled by, or are under common 17 | control with that entity. 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Endoscopy; Microscopy 4 | 5 | |Title|First Author|PDF|Code| 6 | |---|---|---|---| 7 | |A Deep Reinforcement Learning Framework for Frame-by-Frame Plaque Tracking on Intravascular Optical Coherence Tomography Image|Gongning Luo|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_2)|[Code]( https://github.com/luogongning/PlaqueRL)| 8 | |Boundary and Entropy-Driven Adversarial Learning for Fundus Image Segmentation|Shujun Wang|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_12)|[Code]( https://github.com/EmmaW8/BEAL)| 9 | |Probabilistic Atlases to Enforce Topological Constraints|Udaranga Wickramasinghe|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_25)|[Code](https://github.com/cvlab-epfl/PA-net.git)| 10 | |Synapse-Aware Skeleton Generation for Neural Circuits|Brian Matejek|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_26)|[Code](https://www.rhoana.org/synapseaware)| 11 | |Seeing Under the Cover: A Physics Guided Learning Approach for In-bed Pose Estimation|Shuangjun Liu|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_27)|[Code](https://web.northeastern.edu/ostadabbas/2019/06/27/multimodal-in-bedpose-estimation/)| 12 | |Ki-GAN: Knowledge Infusion Generative Adversarial Network for Photoacoustic Image Reconstruction In Vivo|Hengrong Lan|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_31)|[Code](https://github.com/chenyilan/MICCAI19-Ki-GAN)| 13 | |Triple ANet: Adaptive Abnormal-aware Attention Network for WCE Image Classification|Xiaoqing Guo|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_33)|[Code](https://github.com/Guo-Xiaoqing/Triple-ANet)| 14 | |Selective Feature Aggregation Network with Area-Boundary Constraints for Polyp Segmentation|Yuqi Fang|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_34)|[Code]( https://github.com/Yuqi-cuhk/Polyp-Seg)| 15 | |Multi-scale Cell Instance Segmentation with Keypoint Graph Based Bounding Boxes|Jingru Yi|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_41)|[Code](https://github.com/yijingru/KG_Instance_Segmentation)| 16 | |Improving Nuclei/Gland Instance Segmentation in Histopathology Images by Full Resolution Neural Network and Spatial Constrained Loss|Hui Qu|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_42)|[Code](https://github.com/huiqu18/FullNet-varCE)| 17 | |ET-Net: A Generic Edge-aTtention Guidance Network for Medical Image Segmentation|Zhijie Zhang|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_49)|[Code](https://github.com/ZzzJzzZ/ETNet)| 18 | |Instance Segmentation of Biomedical Images with an Object-Aware Embedding Learned with Local Constraints|Long Chen|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_50)|[Code](https://github.com/looooongChen/instance_segmentation_with_pixel_embeddings/)| 19 | |Synthetic Patches, Real Images: Screening for Centrosome Aberrations in EM Images of Human Cancer Cells|Artem Lukoyanov|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_58)|[Code](https://github.com/kreshuklab/centriole_detection)| 20 | |Weakly Supervised Cell Instance Segmentation by Propagating from Detection Response|Kazuya Nishimura|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_72)|[Code]( https://github.com/naivete5656/WSISPDR)| 21 | |Robust Non-negative Tensor Factorization, Diffeomorphic Motion Correction, and Functional Statistics to Understand Fixation in Fluorescence Microscopy|Neel Dey|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_73)|[Code](https://github.com/neel-dey/robustNTF)| 22 | 23 | 24 | 25 | ## [Part II, LNCS Volume 11765](https://link.springer.com/book/10.1007/978-3-030-32245-8) Image Segmentation; Image Registration; Cardiovascular Imaging; Growth, Development, Atrophy, and Progression 26 | 27 | |Title|First Author|PDF|Code| 28 | |---|---|---|---| 29 | |‘Project & Excite’ Modules for Segmentation of Volumetric Medical Scans|Anne-Marie Rickmann|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_5)|[Code](https://github.com/ai-med/squeeze_and_excitation)| 30 | |Assessing Reliability and Challenges of Uncertainty Estimations for Medical Image Segmentation|Alain Jungo|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_6)|[Code](https://github.com/alainjungo/reliability-challenges-uncertainty)| 31 | |Extreme Points Derived Confidence Map as a Cue for Class-Agnostic Interactive Segmentation Using Deep Neural Network|Shadab Khan|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_8)|[Code](https://github.com/ahmedshahin9/AssistedAnnotator)| 32 | |Instance Segmentation from Volumetric Biomedical Images Without Voxel-Wise Labeling|Meng Dong|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_10)|[Code](https://braindata.bitahub.com/)| 33 | |PHiSeg: Capturing Uncertainty in Medical Image Segmentation|Christian F. Baumgartner|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_14)|[Code](https://github.com/baumgach/PHiSeg-code)| 34 | |Automatic Segmentation of Vestibular Schwannoma from T2-Weighted MRI by Deep Spatial Attention with Hardness-Weighted Loss|Guotai Wang|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_30)|[Code](https://github.com/NifTK/VSSegmentation)| 35 | |Learning Shape Representation on Sparse Point Clouds for Volumetric Image Segmentation|Fabian Balsiger|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_31)|[Code](https://github.com/fabianbalsiger/point-cloud-segmentation-miccai2019)| 36 | |3D U2-Net: A 3D Universal U-Net for Multi-domain Medical Image Segmentation|Chao Huang|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_33)|[Code](https://github.com/huangmozhilv/u2net_torch/)| 37 | |Constrained Domain Adaptation for Segmentation|Mathilde Bateson|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_37)|[Code](https://github.com/CDAMICCAI2019/CDA)| 38 | |Curriculum Semi-supervised Segmentation|Hoel Kervadec|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_63)|[Code](https://github.com/LIVIAETS/semi_curriculum)| 39 | |Uncertainty-Aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation|Lequan Yu|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_67)|[Code](https://github.com/yulequan/UA-MT)| 40 | |Deep Probabilistic Modeling of Glioma Growth|Jens Petersen|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_89)|[Code](https://github.com/jenspetersen/probabilistic-unet)| 41 | |Variational AutoEncoder for Regression: Application to Brain Aging Analysis|Qingyu Zhao|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_91)|[Code](https://github.com/QingyuZhao/VAE-for-Regression)| 42 | |Disease Knowledge Transfer Across Neurodegenerative Diseases|R˘azvan V. Marinescu|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_95)|[Code](https://github.com/mrazvan22/dkt)| 43 | |One Network to Segment Them All: A General, Lightweight System for Accurate 3D Medical Image Segmentation|Mathias Perslev|[PDF](https://link.springer.com/chapter/10.1007/978-3-030-32245-8_4)|[TF](https://github.com/perslev/MultiPlanarUNet)| 44 | |Closing the Gap between Deep and Conventional Image Registration using Probabilistic Dense Displacement Networks|Mattias P. Heinrich|[PDF](https://arxiv.org/abs/1907.10931v1)|[Code](https://github.com/multimodallearning/pdd_net)| 45 | 46 | ## [Part III, LNCS Volume 11766](https://link.springer.com/book/10.1007/978-3-030-32248-9) Neuroimage Reconstruction and Synthesis; Neuroimage Segmentation; Diffusion-Weighted Magnetic Resonance Imaging; Functional Neuroimaging (fMRI); Miscellaneous Neuroimaging 47 | 48 | |Title|First Author|PDF|Code| 49 | |---|---|---|---| 50 | |Model-Based Convolutional De-Aliasing Network Learning for Parallel MR Imaging|Yanxia Chen|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_4)|[Code](https://github.com/yanxiachen/ConvDe-AliasingNet)| 51 | |Generation of 3D Brain MRI Using Auto-Encoding Generative Adversarial Networks|Gihyun Kwon|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_14)|[Code](https://github.com/cyclomon/3dbraingen)| 52 | |Predicting the Evolution of White Matter Hyperintensities in Brain MRI Using Generative Adversarial Networks and Irregularity Map|Muhammad Febrian Rachmadi|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_17)|[Code](https://github.com/febrianrachmadi/dep-gan-im)| 53 | |3D Dilated Multi-fiber Network for Real-Time Brain Tumor Segmentation in MRI|Chen Chen|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_21)|[Code](https://github.com/China-LiuXiaopeng/BraTS-DMFNet)| 54 | |Refined Segmentation R-CNN: A Two-Stage Convolutional Neural Network for Punctate White Matter Lesion Segmentation in Preterm Infants|Yalong Liu|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_22)|[Code](https://github.com/YalongLiu/Refined-Segmentation-R-CNN)| 55 | |X-Net: Brain Stroke Lesion Segmentation Based on Depthwise Separable Convolution and Long-Range Dependencies|Kehan Qi|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_28)|[Code](https://github.com/Andrewsher/X-Net)| 56 | |CLCI-Net: Cross-Level Fusion and Context Inference Networks for Lesion Segmentation of Chronic Stroke|Hao Yang|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_30)|[Code](https://github.com/YH0517/CLCI_Net)| 57 | |Unsupervised Deep Learning for Bayesian Brain MRI Segmentation|Adrian V. Dalca|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_40)|[Code](http://voxelmorph.mit.edu)| 58 | |A Partially Reversible U-Net for Memory-Efficient Volumetric Image Segmentation|Robin Brügger|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_48)|[Code](https://github.com/RobinBruegger/PartiallyReversibleUnet)| 59 | |Cortical Surface Parcellation Using Spherical Convolutional Neural Networks|Prasanna Parvathaneni|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_56)|[Code](https://github.com/ilwoolyu/HSD)| 60 | |Deep White Matter Analysis: Fast, Consistent Tractography Segmentation Across Populations and dMRI Acquisitions|Fan Zhang|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_67)|[Code](https://github.com/SlicerDMRI/DeepWMA)| 61 | |DeepTract: A Probabilistic Deep Learning Framework for White Matter Fiber Tractography|Itay Benou|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_70)|[Code](https://github.com/itaybenou/DeepTract.git)| 62 | 63 | 64 | ## [Part IV, LNCS Volume 11767](https://link.springer.com/book/10.1007/978-3-030-32251-9) Shape; Prediction; Detection and Localization; Machine Learning; Computer-Aided Diagnosis; Image Reconstruction and Synthesis 65 | 66 | |Title|First Author|PDF|Code| 67 | |---|---|---|---| 68 | |Multiple Landmark Detection Using Multi-agent Reinforcement Learning|Athanasios Vlontzos|[LNCS](https://doi.org/10.1007/978-3-030-32251-9_29)|[Code](https://github.com/thanosvlo/MARL-for-Anatomical-Landmark-Detection)| 69 | |Unsupervised Anomaly Localization Using Variational Auto-Encoders|David Zimmerer|[LNCS](https://doi.org/10.1007/978-3-030-32251-9_32)|[Code](https://github.com/MIC-DKFZ/vae-anomaly-experiments)| 70 | |Multi-stage Prediction Networks for Data Harmonization|Stefano B. Blumberg|[LNCS](https://doi.org/10.1007/978-3-030-32251-9_45)|[Code](https://github.com/sbb-gh/)| 71 | |Bayesian Volumetric Autoregressive Generative Models for Better Semisupervised Learning|Guilherme Pombo|[LNCS](https://doi.org/10.1007/978-3-030-32251-9_47)|[Code](https://github.com/guilherme-pombo/3DPixelCNN)| 72 | |Overcoming Data Limitation in Medical Visual Question Answering|Binh D. Nguyen|[LNCS](https://doi.org/10.1007/978-3-030-32251-9_57)|[Code](https://github.com/aioz-ai/MICCAI19-MedVQA)| 73 | |VS-Net: Variable Splitting Network for Accelerated Parallel MRI Reconstruction|Jinming Duan|[LNCS](https://doi.org/10.1007/978-3-030-32251-9_78)|[Code](https://github.com/j-duan/VS-Net)| 74 | |Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis|Zongwei Zhou|[PDF](http://www.cs.toronto.edu/~liang/Publications/ModelsGenesis/MICCAI_2019_Full.pdf)|[Keras](https://github.com/MrGiovanni/ModelsGenesis)| 75 | |Multi Scale Curriculum CNN for Context-Aware Breast MRI Malignancy Classification|[Christoph Haarburger](https://scholar.google.com.hk/citations?user=Lb8DcccAAAAJ&hl=en&oi=sra)|[LNCS](https://link.springer.com/chapter/10.1007/978-3-030-32251-9_54), [arXiv](https://arxiv.org/abs/1906.06058)|[PyTorch](https://github.com/haarburger/multi-scale-curriculum)| 76 | 77 | ## [Part V, LNCS Volume 11768](https://link.springer.com/book/10.1007/978-3-030-32254-0) Computer-Assisted Interventions; MIC Meets CAI 78 | 79 | |Title|First Author|PDF|Code| 80 | |---|---|---|---| 81 | |INN: Inflated Neural Networks for IPMN Diagnosis|Rodney LaLonde|[LNCS](https://doi.org/10.1007/978-3-030-32254-0_12)|[Code](https://github.com/lalonderodney/INN-Inflated-Neural-Nets)| 82 | |Generating Large Labeled Data Sets for Laparoscopic Image Processing Tasks Using Unpaired Image-to-Image Translation|Micha Pfeiffer|[LNCS](https://doi.org/10.1007/978-3-030-32254-0_14)|[Code](http://opencas.dkfz.de/image2image/)| 83 | |Variational Shape Completion for Virtual Planning of Jaw Reconstructive Surgery|Amir H. Abdi|[LNCS](https://doi.org/10.1007/978-3-030-32254-0_26)|[Code](https://github.com/amir-abdi/prob-shape-completion)| 84 | |Incorporating Temporal Prior from Motion Flow for Instrument Segmentation in Minimally Invasive Surgery Video|Yueming Jin|[LNCS](https://doi.org/10.1007/978-3-030-32254-0_49)|[Code](https://github.com/keyuncheng/MF-TAPNet)| 85 | |Hard Frame Detection and Online Mapping for Surgical Phase Recognition|Fangqiu Yi|[LNCS](https://doi.org/10.1007/978-3-030-32254-0_50)|[Code](https://github.com/ChinaYi/miccai19)| 86 | |Using 3D Convolutional Neural Networks to Learn Spatiotemporal Features for Automatic Surgical Gesture Recognition in Video|Isabel Funke|[LNCS](https://doi.org/10.1007/978-3-030-32254-0_52)|[Code](https://gitlab.com/nct_tso_public/surgical_gesture_recognition)| 87 | |Matwo-CapsNet: A Multi-label Semantic Segmentation Capsules Network|Savinien Bonheur|[LNCS](https://doi.org/10.1007/978-3-030-32254-0_74)|[Code](https://github.com/savinienb/Matwo-CapsNet)| 88 | |LumiPath – Towards Real-Time Physically-Based Rendering on Embedded Devices|Laura Fink|[LNCS](https://doi.org/10.1007/978-3-030-32254-0_75)|[Code](https://github.com/lorafib/LumiPath)| 89 | 90 | 91 | ## [Part VI, LNCS Volume 11769](https://link.springer.com/book/10.1007/978-3-030-32226-7) Computed Tomography; X-ray Imaging 92 | 93 | |Title|First Author|PDF|Code| 94 | |---|---|---|---| 95 | |ADN: Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction|Haofu Liao|[MICCAI&TMI](https://arxiv.org/abs/1908.01104)|[pytorch](https://github.com/liaohaofu/adn)| 96 | |Adversarial Regression Training for Visualizing the Progression of Chronic Obstructive Pulmonary Disease with Chest X-Rays|Ricardo Bigolin Lanfredi|[LNCS](https://link.springer.com/chapter/10.1007%2F978-3-030-32226-7_76)|[Code](https://github.com/ricbl/vrgan)| 97 | |NoduleNet: Decoupled False Positive Reduction for Pulmonary Nodule Detection and Segmentation |Hao Tang|[LNCS](https://doi.org/10.1007/978-3-030-32226-7_30)|[Code]( https://github.com/uci-cbcl/NoduleNet)| 98 | |Attentive CT Lesion Detection Using Deep Pyramid Inference with Multi-scale Booster |Qingbin Shao|[LNCS](https://doi.org/10.1007/978-3-030-32226-7_34)|[Code]( https://github.com/shaoqb/multi_scale_booster)| 99 | |Misshapen Pelvis Landmark Detection by Spatial Local Correlation Mining for Diagnosing Developmental Dysplasia of the Hip |Chuanbin Liu|[LNCS](https://doi.org/10.1007/978-3-030-32226-7_49)|[Code](https://github.com/liuboss1992/FR-DDH )| 100 | |Adversarial Policy Gradient for Deep Learning Image Augmentation |Kaiyang Cheng|[LNCS](https://doi.org/10.1007/978-3-030-32226-7_50)|[Code](https://github.com/victorychain/Adversarial-Policy-Gradient-Augmentation )| 101 | |Anatomical Priors for Image Segmentation via Post-processing with Denoising Autoencoders |Agostina J. Larrazabal|[LNCS](https://doi.org/10.1007/978-3-030-32226-7_65)|[Code]( https://github.com/dgriffiths3/ml_segmentation)| 102 | |How to Learn from Unlabeled Volume Data: Self-supervised 3D Context Feature Learning |Maximilian Blendowski|[LNCS](https://doi.org/10.1007/978-3-030-32226-7_72)|[Code](https://github.com/multimodallearning/miccai19_self_supervision)| 103 | |Extract Bone Parts Without Human Prior: End-to-end Convolutional Neural Network for Pediatric Bone Age Assessment |Chuanbin Liu|[LNCS](https://doi.org/10.1007/978-3-030-32226-7_74)|[Code](https://github.com/liuboss1992/AR-CNN)| 104 | |Adversarial Regression Training for Visualizing the Progression of Chronic Obstructive Pulmonary Disease with Chest X-Rays |Ricardo Bigolin Lanfredi|[LNCS](https://doi.org/10.1007/978-3-030-32226-7_76)|[Code](https://github.com/ricbl/vrgan)| 105 | |Medical-based Deep Curriculum Learning for Improved Fracture Classification |Amelia Jiménez-Sánchez|[MICCAI](https://link.springer.com/chapter/10.1007/978-3-030-32226-7_77) & [MedIA](https://www.sciencedirect.com/science/article/abs/pii/S1361841521003182)|[Code](https://github.com/ameliajimenez/curriculum-learning-prior-uncertainty)| 106 | 107 | 108 | 109 | 110 | **Any contributions are welcome! Such as arxiv PDF link, new released code and so on.** 111 | -------------------------------------------------------------------------------- /MICCAI-2020.md: -------------------------------------------------------------------------------- 1 | # Word Cloud of MICCAI 2020 Paper Titles 2 | 3 | ![WordCloud-MICCAI2020](https://github.com/JunMa11/MICCAI-OpenSourcePapers/blob/master/WordCloud/WordCloud-MICCAI2020.png) 4 | 5 | # MICCAI 2020 Open Source Papers 6 | 7 | > We use "code" as the keyword to retrieve the open-source papers. Please feel free to pull requests for the unlisted open-source articles. 8 | 9 | 10 | ## [Part I, LNCS Volume 12261: Machine Learning Methodologies](https://link.springer.com/book/10.1007/978-3-030-59710-8) 11 | 12 | 13 | | Title | First Author | PDF | Code | 14 | | ------------------------------------------------------------ | ---------------------- | ---------------------------------------------------- | ------------------------------------------------------------ | 15 | | Scribble2Label: Scribble-Supervised Cell Segmentation via Self-generating Pseudo-Labels with Consistency | Hyeonsoo Lee | [LNCS](https://link.springer.com/chapter/10.1007/978-3-030-59710-8_2) | [Code](https://github.com/hvcl/scribble2label) | 16 | | Are Fast Labeling Methods Reliable? A Case Study of Computer-Aided Expert Annotations on Microscopy Slides | Christian Marzahl | [LNCS](https://doi.org/10.1007/978-3-030-59710-8_3) | [Code]( https://github.com/DeepPathology/Results-Exact-Study) | 17 | | BiO-Net: Learning Recurrent Bi-directional Connections for Encoder-Decoder Architecture | Tiange Xiang | [LNCS](https://doi.org/10.1007/978-3-030-59710-8_8) | [Code](https://github.com/tiangexiang/BiO-Net) | 18 | | Learning Semantics-Enriched Representation via Self-discovery, Self-classification, and Self-restoration | Fatemeh Haghighi | [LNCS](https://doi.org/10.1007/978-3-030-59710-8_14) | [Code](https://github.com/JLiangLab/SemanticGenesis) | 19 | | NAS-SCAM: Neural Architecture Search-Based Spatial and Channel Joint Attention Module for Nuclei Semantic Segmentation and Classification | Zuhao Liu | [LNCS](https://doi.org/10.1007/978-3-030-59710-8_26) | [Code](https://github.com/ZuhaoLiu/NAS-SCAM) | 20 | | Encoding Visual Attributes in Capsules for Explainable Medical Diagnoses | Rodney LaLonde | [LNCS](https://doi.org/10.1007/978-3-030-59710-8_29) | [Code](https://github.com/lalonderodney/X-Caps) | 21 | | Interpretability-Guided Content-Based Medical Image Retrieval | Wilson Silva | [LNCS](https://doi.org/10.1007/978-3-030-59710-8_30) | [Code](https://github.com/wjsilva19/ig_cbir) | 22 | | Comparing to Learn: Surpassing ImageNet Pretraining on Radiographs by Comparing Image Representations | Hong-Yu Zhou | [LNCS](https://doi.org/10.1007/978-3-030-59710-8_39) | [Code](https://github.com/funnyzhou/C2L_MICCAI2020) | 23 | | Scribble-Based Domain Adaptation via Co-segmentation | Reuben Dorent | [LNCS](https://doi.org/10.1007/978-3-030-59710-8_47) | [Code](https://github.com/KCL-BMEIS/ScribbleDA) | 24 | | Source-Relaxed Domain Adaptation for Image Segmentation | Mathilde Bateson | [LNCS](https://doi.org/10.1007/978-3-030-59710-8_48) | [Code](https://github.com/mathilde-b/SRDA) | 25 | | Region-of-Interest Guided Supervoxel Inpainting for Self-supervision | Subhradeep Kayal | [LNCS](https://doi.org/10.1007/978-3-030-59710-8_49) | [Code](https://github.com/DeepK/inpainting) | 26 | | Harnessing Uncertainty in Domain Adaptation for MRI Prostate Lesion Segmentation | Eleni Chiou | [LNCS](https://doi.org/10.1007/978-3-030-59710-8_50) | [Code](https://github.com/elchiou/DA) | 27 | | Deep Semi-supervised Knowledge Distillation for Overlapping Cervical Cell Instance Segmentation | Yanning Zhou | [LNCS](https://doi.org/10.1007/978-3-030-59710-8_51) | [Code](https://github.com/SIAAAAAA/MMT-PSM) | 28 | | Shape-Aware Semi-supervised 3D Semantic Segmentation for Medical Images | Shuailin Li | [LNCS](https://doi.org/10.1007/978-3-030-59710-8_54) | [Code](https://github.com/kleinzcy/SASSnet) | 29 | | Self-supervised Depth Estimation to Regularise Semantic Segmentation in Knee Arthroscopy | Fengbei Liu | [LNCS](https://doi.org/10.1007/978-3-030-59710-8_58) | [Code](https://github.com/ThomasLiu1021/geo-sem) | 30 | | Semi-supervised Medical Image Classification with Global Latent Mixing | Prashnna Kumar Gyawali | [LNCS](https://doi.org/10.1007/978-3-030-59710-8_59) | [Code](https://github.com/Prasanna1991/LatentMixing) | 31 | | Efficient Shapley Explanation for Features Importance Estimation Under Uncertainty | Xiaoxiao Li | [LNCS](https://doi.org/10.1007/978-3-030-59710-8_77) | [Code](https://github.com/xxlya/DistDeepSHAP) | 32 | 33 | 34 | ## [Part II, LNCS Volume 12262: Image Reconstruction and Machine Learning](https://link.springer.com/book/10.1007/978-3-030-59713-9) 35 | 36 | 37 | 38 | | Title | First Author | PDF | Code | 39 | | ------------------------------------------------------------ | ------------------------ | ---------------------------------------------------- | ------------------------------------------------------------ | 40 | | Compressive MR Fingerprinting Reconstruction with Neural Proximal Gradient Iterations | Dongdong Chen | [LNCS](https://doi.org/10.1007/978-3-030-59713-9_2) | [Code](https://github.com/edongdongchen/PGD-Net) | 41 | | BiO-Net: Learning Recurrent Bi-directional Connections for Encoder-Decoder Architecture | Tiange Xiang | [LNCS](https://doi.org/10.1007/978-3-030-59713-9_3) | [Code](https://github.com/facebookresearch/active-mri-acquisition) | 42 | | 3d-SMRnet: Achieving a New Quality of MPI System Matrix Recovery by Deep Learning | Ivo M. Baltruschat | [LNCS](https://doi.org/10.1007/978-3-030-59713-9_8) | [Code](https://github.com/Ivo-B/3dSMRnet) | 43 | | Learned Proximal Networks for Quantitative Susceptibility Mapping | Kuo-Wei Lai | [LNCS](https://doi.org/10.1007/978-3-030-59713-9_13) | [Code](https://github.com/Sulam-Group) | 44 | | Geodesically Smoothed Tensor Features for Pulmonary Hypertension Prognosis Using the Heart and Surrounding Tissues | Johanna Uthoff | [LNCS](https://doi.org/10.1007/978-3-030-59713-9_25) | [Code](https://github.com/pykale) | 45 | | Unlearning Scanner Bias for MRI Harmonisation | Nicola K. Dinsdale | [LNCS](https://doi.org/10.1007/978-3-030-59713-9_36) | [Code](https://github.com/nkdinsdale/Unlearning_for_MRI_harmonisation) | 46 | | Self-supervised Skull Reconstruction in Brain CT Images with Decompressive Craniectomy | Franco Matzkin | [LNCS](https://doi.org/10.1007/978-3-030-59713-9_38) | [Code](http://gitlab.com/matzkin/deep-brain-extractor) | 47 | | Shape-Aware Meta-learning for Generalizing Prostate MRI Segmentation to Unseen Domains | Quande Liu | [LNCS](https://doi.org/10.1007/978-3-030-59713-9_46) | [Code](https://github.com/liuquande/SAML) | 48 | | Joint Modeling of Chest Radiographs and Radiology Reports for Pulmonary Edema Assessment | Geeticka Chauhan | [LNCS](https://doi.org/10.1007/978-3-030-59713-9_51) | [Code](https://github.com/RayRuizhiLiao/joint_chestxray) | 49 | | Large-Scale Inference of Liver Fat with Neural Networks on UK Biobank Body MRI | Taro Langner | [LNCS](https://doi.org/10.1007/978-3-030-59713-9_58) | [Code](https://github.com/tarolangner/mri-biometry) | 50 | | Interpretation of Disease Evidence for Medical Images Using Adversarial Deformation Fields | Ricardo Bigolin Lanfredi | [LNCS](https://doi.org/10.1007/978-3-030-59713-9_71) | [Code](https://github.com/ricbl/defigan) | 51 | 52 | 53 | 54 | ## [Part III, LNCS Volume 12263: Computer Aided Intervention, Ultrasound and Image Registration](https://link.springer.com/book/10.1007/978-3-030-59716-0) 55 | 56 | 57 | 58 | | Title | First Author | PDF | Code | 59 | | ------------------------------------------------------------ | --------------------- | ---------------------------------------------------- | ------------------------------------------------------------ | 60 | | Reconstructing Sinus Anatomy from Endoscopic Video – Towards a Radiation-Free Approach for Quantitative Longitudinal Assessment | Xingtong Liu | [LNCS](https://doi.org/10.1007/978-3-030-59716-0_1) | [Code](https://github.com/lppllppl920/DenseReconstruction-Pytorch) | 61 | | Simulation of Brain Resection for Cavity Segmentation Using Self-supervised and Semi-supervised Learning | Fernando Pérez-Garcı́a | [LNCS](https://doi.org/10.1007/978-3-030-59716-0_12) | [Code](https://github.com/fepegar/resector) | 62 | | MvMM-RegNet: A New Image Registration Framework Based on Multivariate Mixture Model and Neural Network Estimation | Xinzhe Luo | [LNCS](https://doi.org/10.1007/978-3-030-59716-0_15) | [Code](https://zmiclab.github.io/projects.html) | 63 | | Highly Accurate and Memory Efficient Unsupervised Learning-Based Discrete CT Registration Using 2.5D Displacement Search | Mattias P. Heinrich | [LNCS](https://doi.org/10.1007/978-3-030-59716-0_19) | [Code](https://github.com/multimodallearning/pdd2.5/) | 64 | | Generalizing Spatial Transformers to Projective Geometry with Applications to 2D/3D Registration | Cong Gao | [LNCS](https://doi.org/10.1007/978-3-030-59716-0_32) | [Code](https://github.com/gaocong13/Projective-Spatial-Transformers) | 65 | | TeCNO: Surgical Phase Recognition with Multi-stage Temporal Convolutional Networks | Tobias Czempiel | [LNCS](https://doi.org/10.1007/978-3-030-59716-0_33) | [Code](https://github.com/tobiascz/TeCNO/) | 66 | | AutoSNAP: Automatically Learning Neural Architectures for Instrument Pose Estimation | David Kugler | [LNCS](https://doi.org/10.1007/978-3-030-59716-0_36) | [Code](https://github.com/MECLabTUDA/AutoSNAP) | 67 | | Sensorless Freehand 3D Ultrasound Reconstruction via Deep Contextual Learning | Hengtao Guo | [LNCS](https://doi.org/10.1007/978-3-030-59716-0_44) | [Code](https://github.com/DIAL-RPI/FreehandUSRecon) | 68 | | ISINet: An Instance-Based Approach for Surgical Instrument Segmentation | Cristina Gonza'lez | [LNCS](https://doi.org/10.1007/978-3-030-59716-0_57) | [Code](https://github.com/BCV-Uniandes/ISINet) | 69 | | Vision-Based Estimation of MDS-UPDRS Gait Scores for Assessing Parkinson’s Disease Motor Severity | Mandy Lu | [LNCS](https://doi.org/10.1007/978-3-030-59716-0_61) | [Code](https://github.com/mlu355/PD-Motor-Severity-Estimation) | 70 | | Towards Accurate and Interpretable Surgical Skill Assessment: A Video-Based Method Incorporating Recognized Surgical Gestures and Skill Levels | Tianyu Wang | [LNCS](https://doi.org/10.1007/978-3-030-59716-0_64) | [Code](https://github.com/gunnerwang/MTL-VF-and-IMTL-AGF) | 71 | | Learning Motion Flows for Semi-supervised Instrument Segmentation from Robotic Surgical Video | Zixu Zhao | [LNCS](https://doi.org/10.1007/978-3-030-59716-0_65) | [Code](https://github.com/zxzhaoeric/Semi-InstruSeg) | 72 | | Rethinking Anticipation Tasks: Uncertainty-Aware Anticipation of Sparse Surgical Instrument Usage for Context-Aware Assistance | Dominik Rivoir | [LNCS](https://doi.org/10.1007/978-3-030-59716-0_72) | [Code](https://www.gitlab.com/nct_tso_public/ins_ant) | 73 | 74 | 75 | ## [Part IV, LNCS Volume 12264: Segmentation and Shape Analysis](https://link.springer.com/book/10.1007/978-3-030-59719-1) 76 | 77 | 78 | 79 | | Title | First Author | PDF | Code | 80 | | ------------------------------------------------------------ | ----------------- | ---------------------------------------------------- | ------------------------------------------------------------ | 81 | | DeScarGAN: Disease-Specific Anomaly Detection with Weak Supervision | Julia Wolleb | [LNCS](https://doi.org/10.1007/978-3-030-59719-1_2) | [Code](https://github.com/JuliaWolleb/DeScarGAN) | 82 | | Learning Directional Feature Maps for Cardiac MRI Segmentation | Feng Cheng | [LNCS](https://doi.org/10.1007/978-3-030-59719-1_11) | [Code](https://github.com/c-feng/DirectionalFeature) | 83 | | Uncertainty-Guided Efficient Interactive Refinement of Fetal Brain Segmentation from Stacks of MRI Slices | Guotai Wang | [LNCS](https://doi.org/10.1007/978-3-030-59719-1_28) | [Code](https://github.com/HiLab-git/UGIR) | 84 | | Defending Deep Learning-Based Biomedical Image Segmentation from Adversarial Attacks: A Low-Cost Frequency Refinement Approach | Qi Liu | [LNCS](https://doi.org/10.1007/978-3-030-59719-1_34) | [Code](https://github.com/qiliu08/frequency-refinement-defense) | 85 | | Asymmetrical Multi-task Attention U-Net for the Segmentation of Prostate Bed in CT Image | Xuanang Xu | [LNCS](https://doi.org/10.1007/978-3-030-59719-1_46) | [Code](https://github.com/superxuang/amta-net) | 86 | | Generation of Annotated Brain Tumor MRIs with Tumor-induced Tissue Deformations for Training and Assessment of Neural Networks | Hristina Uzunova | [LNCS](https://doi.org/10.1007/978-3-030-59719-1_49) | [Code](https://github.com/hristina-uzunova/TumorMassEffect) | 87 | | AlignShift: Bridging the Gap of Imaging Thickness in 3D Anisotropic Volumes | Jiancheng Yang | [LNCS](https://doi.org/10.1007/978-3-030-59719-1_55) | [Code](https://github.
com/M3DV/AlignShift) | 88 | | Automated Detection of Cortical Lesions in Multiple Sclerosis Patients with 7T MRI | Francesco La Rosa | [LNCS](https://doi.org/10.1007/978-3-030-59719-1_57) | [Code](https://github.com/Medical-Image-Analysis-Laboratory) | 89 | | Miss the Point: Targeted Adversarial Attack on Multiple Landmark Detection | Qingsong Yao | [LNCS](https://doi.org/10.1007/978-3-030-59719-1_67) | [Code](https://github.com/qsyao/attack_landmark_detection) | 90 | | Non-Rigid Volume to Surface Registration Using a Data-Driven Biomechanical Model | Micha Pfeiffer | [LNCS](https://doi.org/10.1007/978-3-030-59719-1_70) | [Code](https://gitlab.com/nct_tso_public/Volume2SurfaceCNN) | 91 | | A Kernelized Multi-level Localization Method for Flexible Shape Modeling with Few Training Data | Matthias Wilms | [LNCS](https://doi.org/10.1007/978-3-030-59719-1_74) | [Code](https://github.com/wilmsm/localizedssm) | 92 | | iU-Net: Towards Accurate Segmentation of Biomedical Images Using Over-Complete Representations | Jeya Maria Jose Valanarasu | [LNCS](https://link.springer.com/chapter/10.1007/978-3-030-59719-1_36) | [Code](https://github.com/jeya-maria-jose/KiU-Net-pytorch) | 93 | 94 | 95 | ## [Part V, LNCS Volume 12265: Biological, Optical and Microscopic Image Analysis](https://link.springer.com/book/10.1007/978-3-030-59722-1) 96 | 97 | 98 | 99 | | Title | First Author | PDF | Code | 100 | | ------------------------------------------------------------ | -------------------- | ---------------------------------------------------- | ------------------------------------------------------------ | 101 | | Demixing Calcium Imaging Data in C. elegans via Deformable Non-negative Matrix Factorization | Amin Nejatbakhsh | [LNCS](https://doi.org/10.1007/978-3-030-59722-1_2) | [Code](https://github.com/amin-nejat/dNMF) | 102 | | MitoEM Dataset: Large-Scale 3D Mitochondria Instance Segmentation from EM Images | Donglai Wei | [LNCS](https://doi.org/10.1007/978-3-030-59722-1_7) | [Code](https://donglaiw.github.io/page/mitoEM/index.html) | 103 | | Microtubule Tracking in Electron Microscopy Volumes | Nils Eckstein | [LNCS](https://doi.org/10.1007/978-3-030-59722-1_10) | [Code](https://github.com/nilsec/micron) | 104 | | Statistical Atlas of C. elegans Neurons | Erdem Varol | [LNCS](https://doi.org/10.1007/978-3-030-59722-1_12) | [Code](https://github.com/amin-nejat/StatAtlas) | 105 | | Probabilistic Joint Segmentation and Labeling of C. elegans Neurons | Amin Nejatbakhsh | [LNCS](https://doi.org/10.1007/978-3-030-59722-1_13) | [Code](https://github.com/amin-nejat/SinkhornEM) | 106 | | Joint Spatial-Wavelet Dual-Stream Network for Super-Resolution | Zhen Chen | [LNCS](https://doi.org/10.1007/978-3-030-59722-1_18) | [Code](https://github.com/franciszchen/SWD-Net) | 107 | | Towards Neuron Segmentation from Macaque Brain Images: A Weakly Supervised Approach | Meng Dong | [LNCS](https://doi.org/10.1007/978-3-030-59722-1_19) | [Code](https://braindata.bitahub.com/) | 108 | | 3D Reconstruction and Segmentation of Dissection Photographs for MRI-Free Neuropathology | Henry F. J. Tregidgo | [LNCS](https://doi.org/10.1007/978-3-030-59722-1_20) | [Code](https://github.com/htregidgo/DissectionPhotoVolumes) | 109 | | Boundary-Assisted Region Proposal Networks for Nucleus Segmentation | Shengcong Chen | [LNCS](https://doi.org/10.1007/978-3-030-59722-1_27) | [Code](https://github.com/csccsccsccsc/brpnet) | 110 | | Weakly-Supervised Nucleus Segmentation Based on Point Annotations: A Coarse-to-Fine Self-Stimulated Learning Strategy | Kuan Tian | [LNCS](https://doi.org/10.1007/978-3-030-59722-1_29) | [Code](https://github.com/tiankuan93/C2FNet) | 111 | | Self-supervised Nuclei Segmentation in Histopathological Images Using Attention | Mihir Sahasrabudhe | [LNCS](https://doi.org/10.1007/978-3-030-59722-1_38) | [Code](https://github.com/msahasrabudhe/miccai2020_self_sup_nuclei_seg) | 112 | | Renal Cell Carcinoma Detection and Subtyping with Minimal Point-Based Annotation in Whole-Slide Images | Zeyu Gao | [LNCS](https://doi.org/10.1007/978-3-030-59722-1_42) | [Code](https://gitlab.com/BioAI/RCC_DS) | 113 | | Tracing Diagnosis Paths on Histopathology WSIs for Diagnostically Relevant Case Recommendation | Yushan Zheng | [LNCS](https://doi.org/10.1007/978-3-030-59722-1_44) | [Code](https://github.com/Zhengyushan/dpathnet) | 114 | | Weakly Supervised Multiple Instance Learning Histopathological Tumor Segmentation | Marvin Lerousseau | [LNCS](https://doi.org/10.1007/978-3-030-59722-1_45) | [Code](https://github.com/marvinler/tcga_segmentation) | 115 | | Divide-and-Rule: Self-Supervised Learning for Survival Analysis in Colorectal Cancer | Christian Abbet | [LNCS](https://doi.org/10.1007/978-3-030-59722-1_46) | [Code](https://github.com/christianabbet/DnR) | 116 | | Foveation for Segmentation of Mega-Pixel Histology Images | Chen Jin | [LNCS](https://doi.org/10.1007/978-3-030-59722-1_54) | [Code](https://github.com/lxasqjc/Foveation-for-Segmentation-of-Mega-pixel-Histology-Images) | 117 | | Anterior Segment Eye Lesion Segmentation with Advanced Fusion Strategies and Auxiliary Tasks | Ke Wang | [LNCS](https://doi.org/10.1007/978-3-030-59722-1_63) | [Code](https://github.com/kaisadadi/Anterior-Segment-Eye-Lesion-Segmentation) | 118 | 119 | 120 | 121 | ## [Part VI, LNCS Volume 12266: Clinical Applications](https://link.springer.com/book/10.1007/978-3-030-59725-2) 122 | 123 | 124 | 125 | | Title | First Author | PDF | Code | 126 | | ------------------------------------------------------------ | ------------------- | ---------------------------------------------------- | ------------------------------------------------------------ | 127 | | Branch-Aware Double DQN for Centerline Extraction in Coronary CT Angiography | Yuyang Zhang | [LNCS](https://doi.org/10.1007/978-3-030-59725-2_4) | [Code](https://github.com/514sz/Branch-aware-centerline-extraction) | 128 | | Automated Intracranial Artery Labeling Using a Graph Neural Network and Hierarchical Refinement | Li Chen | [LNCS](https://doi.org/10.1007/978-3-030-59725-2_8) | [Code](https://github.com/clatfd/GNN-ART-LABEL) | 129 | | Adaptive Context Selection for Polyp Segmentation | Ruifei Zhang | [LNCS](https://doi.org/10.1007/978-3-030-59725-2_25) | [Code](https://github.com/ReaFly/ACSNet) | 130 | | Data-Driven Multi-contrast Spectral Microstructure Imaging with InSpect | Paddy J. Slator | [LNCS](https://doi.org/10.1007/978-3-030-59725-2_36) | [Code](https://github.com/PaddySlator/inspect) | 131 | | Region Proposals for Saliency Map Refinement for Weakly-Supervised Disease Localisation and Classification | Renato Hermoza | [LNCS](https://doi.org/10.1007/978-3-030-59725-2_52) | [Code](https://github.com/renato145/RpSalWeaklyDet) | 132 | | Class-Aware Multi-window Adversarial Lung Nodule Synthesis Conditioned on Semantic Features | Qiuli Wang | [LNCS](https://doi.org/10.1007/978-3-030-59725-2_57) | [Code](https://github.com/qiuliwang/CA-MW-Adversarial-Synthesis) | 133 | | SIMBA: Specific Identity Markers for Bone Age Assessment | Cristina Gonz´ alez | [LNCS](https://doi.org/10.1007/978-3-030-59725-2_73) | [Code](https://github.com/BCV-Uniandes/SIMBA) | 134 | | Time Matters: Handling Spatio-Temporal Perfusion Information for Automated TICI Scoring | Maximilian Nielsen | [LNCS](https://doi.org/10.1007/978-3-030-59725-2_9) | [Code](https://github.com/autoTICI) | 135 | | Decoupling Inherent Risk and Early Cancer Signs in Image-Based Breast Cancer Risk Models | Yue Liu | [LNCS](https://doi.org/10.1007/978-3-030-59725-2_23) | [Code](https://github.com/yueliukth/decoupling_breast_cancer_risk) | 136 | | PraNet: Parallel Reverse Attention Network for Polyp Segmentation | Deng-Ping Fan | [LNCS](https://doi.org/10.1007/978-3-030-59725-2_26) | [Code](https://github.com/DengPingFan/PraNet) | 137 | | Few-Shot Anomaly Detection for Polyp Frames from Colonoscopy | Yu Tian | [LNCS](https://doi.org/10.1007/978-3-030-59725-2_27) | [Code](https://github.com/tianyu0207/FSAD-Net) | 138 | | Keypoints Localization for Joint Vertebra Detection and Fracture Severity Quantification | Maxim Pisov | [LNCS](https://doi.org/10.1007/978-3-030-59725-2_70) | [Code](https://github.com/neuro-ml/vertebral-fractures-severity) | 139 | | Generative Modelling of 3D In-Silico Spongiosa with Controllable Micro-structural Parameters | Emmanuel Iarussi | [LNCS](https://doi.org/10.1007/978-3-030-59725-2_76) | [Code](http://github.com/emmanueliarussi/generative3DSpongiosa) | 140 | 141 | 142 | 143 | ## [Part VII, LNCS Volume 12267: Neurological Imaging and PET](https://link.springer.com/book/10.1007/978-3-030-59728-3) 144 | 145 | 146 | 147 | | Title | First Author | PDF | Code | 148 | | ------------------------------------------------------------ | -------------------- | ---------------------------------------------------- | ------------------------------------------------------------ | 149 | | From Connectomic to Task-Evoked Fingerprints: Individualized Prediction of Task Contrasts from Resting-State Functional Connectivity | Gia H. Ngo | [LNCS](https://doi.org/10.1007/978-3-030-59728-3_7) | [Code](https://github.com/ngohgia/brain-surf-cnn) | 150 | | Deep Graph Normalizer: A Geometric Deep Learning Approach for Estimating Connectional Brain Templates | Mustafa Burak Gurbuz | [LNCS](https://doi.org/10.1007/978-3-030-59728-3_16) | [Code](https://github.com/basiralab/DGN) | 151 | | Supervised Multi-topology Network Cross-Diffusion for Population-Driven Brain Network Atlas Estimation | Islem Mhiri | [LNCS](https://doi.org/10.1007/978-3-030-59728-3_17) | [Code](https://github.com/basiralab/SM-netFusion) | 152 | | Partial Volume Segmentation of Brain MRI Scans of Any Resolution and Contrast | Benjamin Billot | [LNCS](https://doi.org/10.1007/978-3-030-59728-3_18) | [Code](https://github.com/BBillot/SynthSeg) | 153 | | Context-Aware Refinement Network Incorporating Structural Connectivity Prior for Brain Midline Delineation | Shen Wang | [LNCS](https://doi.org/10.1007/978-3-030-59728-3_21) | [Code](https://github.com/ShawnBIT/Brain-Midline-Detection) | 154 | | White Matter Tract Segmentation with Self-supervised Learning | Qi Lu | [LNCS](https://doi.org/10.1007/978-3-030-59728-3_27) | [Code](https://github.com/MIC-DKFZ/TractSeg) | 155 | | Tractogram Filtering of Anatomically Non-plausible Fibers with Geometric Deep Learning | Pietro Astolfi | [LNCS](https://doi.org/10.1007/978-3-030-59728-3_29) | [Code](https://github.com/FBK-NILab/tractogram_filtering/tree/miccai2020) | 156 | | TRAKO: Efficient Transmission of Tractography Data for Visualization | Daniel Haehn | [LNCS](https://doi.org/10.1007/978-3-030-59728-3_32) | [Code](https://github.com/bostongfx/trako) | 157 | | Whole MILC: Generalizing Learned Dynamics Across Tasks, Datasets, and Populations | Usman Mahmood | [LNCS](https://doi.org/10.1007/978-3-030-59728-3_40) | [Code](https://github.com/UsmanMahmood27/MILC) | 158 | | A Deep Pattern Recognition Approach for Inferring Respiratory Volume Fluctuations from fMRI Data | Roza G. Bayrak | [LNCS](https://doi.org/10.1007/978-3-030-59728-3_42) | [Code](https://github.com/neurdylab/deep-physio-recon) | 159 | | Spatio-Temporal Graph Convolution for Resting-State fMRI Analysis | Soham Gadgil | [LNCS](https://doi.org/10.1007/978-3-030-59728-3_52) | [Code](https://github.com/sgadgil6/cnslab_fmri) | 160 | | A Shared Neural Encoding Model for the Prediction of Subject-Specific fMRI Response | Meenakshi Khosla | [LNCS](https://doi.org/10.1007/978-3-030-59728-3_53) | [Code](https://github.com/mk2299/SharedEncoding_MICCAI) | 161 | | Topology-Aware Generative Adversarial Network for Joint Prediction of Multiple Brain Graphs from a Single Brain Graph | Alaa Bessadok | [LNCS](https://doi.org/10.1007/978-3-030-59728-3_54) | [Code](https://github.com/basiralab/MultiGraphGAN) | 162 | | Patch-Based Abnormality Maps for Improved Deep Learning-Based Classification of Huntington’s Disease | Kilian Hett | [LNCS](https://doi.org/10.1007/978-3-030-59728-3_62) | [Code](https://github.com/MedICL-VU/patch-based_abnormality) | 163 | | Modelling the Distribution of 3D Brain MRI Using a 2D Slice VAE | Anna Volokitin | [LNCS](https://doi.org/10.1007/978-3-030-59728-3_64) | [Code](https://github.com/voanna/slices-to-3d-brain-vae/) | 164 | | Image-Level Harmonization of Multi-site Data Using Image-and-Spatial Transformer Networks | Robert Robinson | [LNCS](https://doi.org/10.1007/978-3-030-59728-3_69) | [Code](https://github.com/mlnotebook/domain_adapation_istn) | 165 | -------------------------------------------------------------------------------- /MICCAI-2022.md: -------------------------------------------------------------------------------- 1 | # MICCAI 2022 Open-Source Papers 2 | 3 | ![wordcloud22](https://github.com/JunMa11/MICCAI-OpenSourcePapers/blob/master/WordCloud/WordCloud-MICCAI2022.png) 4 | 5 | > We use "Link to the code repository" in [MICCAI 2022 Accepted Papers and Reviews](https://conferences.miccai.org/2022/papers/) as the keyword to retrieve the open-source papers. Please feel free to pull requests for the unlisted open-source papers. 6 | 7 | 8 | 9 | | Title | FirstAuthor | Code | 10 | | :----------------------------------------------------------- | :------------------------- | :----------------------------------------------------------- | 11 | | [3D CVT-GAN: A 3D Convolutional Vision Transformer-GAN for PET Reconstruction](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_49) | Pinxian Zeng | [code](https://github.com/Aru321/CVTGAN) | 12 | | [3D Global Fourier Network for Alzheimer's Disease Diagnosis using Structural MRI](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_4) | Shengjie Zhang | [code](https://github.com/qbmizsj/GFNet) | 13 | | [4D-OR: Semantic Scene Graphs for OR Domain Modeling](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_45) | Ege Özsoy | [code](https://github.com/egeozsoy/4D-OR) | 14 | | [A Comprehensive Study of Modern Architectures and Regularization Approaches on CheXpert5000](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_62) | Sontje Ihler | [code](https://gitlab.uni-hannover.de/sontje.ihler/chexpert5000) | 15 | | [A Deep-Discrete Learning Framework for Spherical Surface Registration](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_12) | Mohamed A. Suliman | [code](https://github.com/mohamedasuliman/DDR/) | 16 | | [A Hybrid Propagation Network for Interactive Volumetric Image Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_64) | Luyue Shi | [code](https://github.com/luyueshi/Hybrid-Propagation) | 17 | | [A Medical Semantic-Assisted Transformer for Radiographic Report Generation](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_63) | Zhanyu Wang | [code](https://github.com/zwan0839/MSAT) | 18 | | [A Multi-task Network with Weight Decay Skip Connection Training for Anomaly Detection in Retinal Fundus Images](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_63) | Wentian Zhang | [code](https://github.com/WentianZhang-ML/WDMT-Net) | 19 | | [A New Dataset and A Baseline Model for Breast Lesion Detection in Ultrasound Videos](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_59) | Zhi Lin | [code](https://github.com/jhl-Det/CVA-Net) | 20 | | [A Novel Fusion Network for Morphological Analysis of Common Iliac Artery](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_6) | Meng Song | [code](https://github.com/SongCASIA/FTU_Net) | 21 | | [A Novel Knowledge Keeper Network for 7T-Free But 7T-Guided Brain Tissue Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_32) | Jieun Lee | [code](https://github.com/2jieun2/knowledge_keeper) | 22 | | [A Penalty Approach for Normalizing Feature Distributions to Build Confounder-Free Models](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_37) | Anthony Vento | [code](https://github.com/mlu355/MetadataNorm/blob/main/synthetic_dataset.py) | 23 | | [A Robust Volumetric Transformer for Accurate 3D Tumor Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_16) | Himashi Peiris | [code](https://github.com/himashi92/VT-UNet) | 24 | | [A Self-Guided Framework for Radiology Report Generation](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_56) | Jun Li | [code](https://github.com/LijunRio/A-Self-Guided-Framework) | 25 | | [A Sense of Direction in Biomedical Neural Networks](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_8) | Zewen Liu | [code](https://github.com/Zewen-Liu/MASC-Unit) | 26 | | [A Transformer-Based Iterative Reconstruction Model for Sparse-View CT Reconstruction](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_75) | Wenjun Xia | [code](https://github.com/Deep-Imaging-Group/RegFormer) | 27 | | [AANet: Artery-Aware Network for Pulmonary Embolism Detection in CTPA Images](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_45) | Jia Guo | [code](https://github.com/guojiajeremy/AANet) | 28 | | [Accelerated pseudo 3D dynamic speech MR imaging at 3T using unsupervised deep variational manifold learning](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_66) | Rushdi Zahid Rusho | [code](https://github.com/rushdi-rusho/varMRI/tree/main/SpeechDatasets) | 29 | | [Accurate and Robust Lesion RECIST Diameter Prediction and Segmentation with Transformers](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_51) | Youbao Tang | [code](https://github.com/JimmyCai91/DLT) | 30 | | [Accurate Corresponding Fiber Tract Segmentation via FiberGeoMap Learner](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_14) | Zhenwei Wang | [code](https://github.com/Garand0o0/FiberTractSegmentation) | 31 | | [Adapting the Mean Teacher for keypoint-based lung registration under geometric domain shifts](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_27) | Alexander Bigalke | [code](https://github.com/multimodallearning/registration-da-mean-teacher) | 32 | | [Adaptive 3D Localization of 2D Freehand Ultrasound Brain Images](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_20) | Pak-Hei Yeung | [code](https://github.com/pakheiyeung/AdLocUI) | 33 | | [AdaTriplet: Adaptive Gradient Triplet Loss with Automatic Margin Learning for Forensic Medical Image Matching](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_69) | Khanh Nguyen | [code](https://github.com/Oulu-IMEDS/AdaTriplet) | 34 | | [Adversarially Robust Prototypical Few-shot Segmentation with Neural-ODEs](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_8) | Prashant Pandey | [code](https://github.com/prinshul/Prototype_NeuralODE_Adv_Attack) | 35 | | [An Advanced Deep Learning Framework for Video-based Diagnosis of ASD](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_42) | Miaomiao Cai | [code](https://github.com/xiaotaiyangcmm/DASD) | 36 | | [An End-to-End Combinatorial Optimization Method for R-band Chromosome Recognition with Grouping Guided Attention](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_1) | Chao Xia | [code](https://github.com/xiabc612/R-band-chromosome-recognition) | 37 | | [An Inclusive Task-Aware Framework for Radiology Report Generation](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_54) | Lin Wang | [code](https://github.com/Reremee/ITA) | 38 | | [An Optimal Control Problem for Elastic Registration and Force Estimation in Augmented Surgery](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_8) | Guillaume Mestdagh | [code](https://github.com/gmestdagh/adjoint-elastic-registration) | 39 | | [Analyzing Brain Structural Connectivity as Continuous Random Functions](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_27) | William Consagra | [code](https://github.com/sbci-brain/SBCI_Modeling_FPCA) | 40 | | [Anatomy-Guided Weakly-Supervised Abnormality Localization in Chest X-rays](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_63) | Ke Yu | [code](https://github.com/batmanlab/AGXNet) | 41 | | [Anomaly-aware multiple instance learning for rare anemia disorder classification](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_33) | Salome Kazeminia | [code](https://github.com/marrlab/Anomaly-aware-MIL) | 42 | | [Asymmetry Disentanglement Network for Interpretable Acute Ischemic Stroke Infarct Segmentation in Non-Contrast CT Scans](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_40) | Haomiao Ni | [code](https://github.com/nihaomiao/MICCAI22_ADN) | 43 | | [Atlas-based Semantic Segmentation of Prostate Zones](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_55) | Jiazhen Zhang | [code](https://github.com/OnofreyLab/prostate_atlas_segm_miccai2022) | 44 | | [Attention-enhanced Disentangled Representation Learning for Unsupervised Domain Adaptation in Cardiac Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_71) | Xiaoyi Sun | [code](https://github.com/Sunxy11/ADR) | 45 | | [Autofocusing+: Noise-Resilient Motion Correction in Magnetic Resonance Imaging](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_35) | Ekaterina Kuzmina | [code](https://github.com/cviaai/AF-PLUS) | 46 | | [Automated Classification of General Movements in Infants Using Two-stream Spatiotemporal Fusion Network](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_72) | Yuki Hashimoto | [code](https://github.com/uoNuM/two-stream-gma) | 47 | | [Automatic Detection of Steatosis in Ultrasound Images with Comparative Visual Labeling](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_39) | Güinther Saibro | [code](https://github.com/IRCAD/cvl) | 48 | | [Automatic identification of segmentation errors for radiotherapy using geometric learning](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_31) | Edward G. A. Henderson | [code](https://github.com/deepmind/tcia-ct-scan-dataset) | 49 | | [BabyNet: Residual Transformer Module for Birth Weight Prediction on Fetal Ultrasound Video](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_34) | Szymon Płotka | [code](https://github.com/SanoScience/BabyNet) | 50 | | [Bayesian dense inverse searching algorithm for real-time stereo matching in minimally invasive surgery](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_32) | Jingwei Song | [code](https://github.com/JingweiSong/BDIS.git) | 51 | | [Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi-Supervised Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_56) | Mou-Cheng Xu | [code](https://github.com/moucheng2017/EMSSL) | 52 | | [Benchmarking the Robustness of Deep Neural Networks to Common Corruptions in Digital Pathology](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_24) | Yunlong Zhang | [code](https://github.com/superjamessyx/robustness_benchmark) | 53 | | [BERTHop: An Effective Vision-and-Language Model for Chest X-ray Disease Diagnosis](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_69) | Masoud Monajatipoor | [code](https://github.com/monajati/BERTHop) | 54 | | [BiometryNet: Landmark-based Fetal Biometry Estimation from Standard Ultrasound Planes](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_27) | Netanell Avisdris | [code](https://github.com/netanellavisdris/fetalbiometry) | 55 | | [BMD-GAN: Bone mineral density estimation using x-ray image decomposition into projections of bone-segmented quantitative computed tomography using hierarchical learning](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_61) | Yi Gu | [code](https://github.com/NAIST-ICB/BMD-GAN) | 56 | | [Boundary-Enhanced Self-Supervised Learning for Brain Structure Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_2) | Feng Chang | [code](https://github.com/changfeng3168/BE-SSL) | 57 | | [Brain-Aware Replacements for Supervised Contrastive Learning in Detection of Alzheimer's Disease](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_44) | Mehmet Saygın Seyfioğlu | [code](https://github.com/aldraus/BrainAwareReplacementsForAD) | 58 | | [CACTUSS: Common Anatomical CT-US Space for US examinations](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_47) | Yordanka Velikova | [code](https://github.com/danivelikova/cactuss) | 59 | | [Calibrating Label Distribution for Class-Imbalanced Barely-Supervised Knee Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_11) | Yiqun Lin | [code](https://github.com/xmed-lab/CLD-Semi) | 60 | | [Camera Adaptation for Fundus-Image-Based CVD Risk Estimation](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_57) | Zhihong Lin | [code](https://github.com/linzhlalala/CVD-risk-based-on-retinal-fundus-images) | 61 | | [Capturing Shape Information with Multi-Scale Topological Loss Terms for 3D Reconstruction](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_15) | Dominik J. E. Waibel | [code](https://github.com/marrlab/SHAPR_torch) | 62 | | [CaRTS: Causality-driven Robot Tool Segmentation from Vision and Kinematics Data](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_37) | Hao Ding | [code](https://github.com/hding2455/CaRTS) | 63 | | [CASHformer: Cognition Aware SHape Transformer for Longitudinal Analysis](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_5) | Ignacio Sarasua | [code](https://github.com/ai-med) | 64 | | [Censor-aware Semi-supervised Learning for Survival Time Prediction from Medical Images](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_21) | Renato Hermoza | [code](https://github.com/renato145/CASurv) | 65 | | [CFDA: Collaborative Feature Disentanglement and Augmentation for Pulmonary Airway Tree Modeling of COVID-19 CTs](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_48) | Minghui Zhang | [code](https://github.com/Puzzled-Hui/CFDA) | 66 | | [CheXRelNet: An Anatomy-Aware Model for Tracking Longitudinal Relationships between Chest X-Rays](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_55) | Gaurang Karwande | [code](https://github.com/PLAN-Lab/ChexRelNet) | 67 | | [ChrSNet: Chromosome Straightening using Self-attention Guided Networks](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_12) | Sunyi Zheng | [code](https://github.com/lijx1996/ChrSNet) | 68 | | [CIRDataset: A large-scale Dataset for Clinically-Interpretable lung nodule Radiomics and malignancy prediction](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_2) | Wookjin Choi | [code](https://github.com/nadeemlab/CIR) | 69 | | [Class Impression for Data-free Incremental Learning](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_31) | Sana Ayromlou | [code](https://github.com/sanaAyrml/Class-Impresion-for-Data-free-Incremental-Learning.git) | 70 | | [CLTS-GAN: Color-Lighting-Texture-Specular Reflection Augmentation for Colonoscopy](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_49) | Shawn Mathew | [code](https://github.com/nadeemlab/CEP) | 71 | | [Combining multiple atlases to estimate data-driven mappings between functional connectomes using optimal transport](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_37) | Javid Dadashkarimi | [code](https://github.com/dadashkarimi/carot) | 72 | | [Computer-aided Tuberculosis Diagnosis with Attribute Reasoning Assistance](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_59) | Chengwei Pan | [code](https://github.com/GangmingZhao/tb-attribute-weak-localization) | 73 | | [Conditional VAEs for confound removal and normative modelling of neurodegenerative diseases](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_41) | Ana Lawry Aguila | [code](https://github.com/alawryaguila/normativecVAE) | 74 | | [Consistency-preserving Visual Question Answering in Medical Imaging](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_37) | Sergio Tascon-Morales | [code](https://github.com/sergiotasconmorales/consistency_vqa) | 75 | | [Contrastive Functional Connectivity Graph Learning for Population-based fMRI Classification](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_21) | Xuesong Wang | [code](https://github.com/xuesongwang/Contrastive-Functional-Connectivity-Graph-Learning) | 76 | | [Contrastive learning for echocardiographic view integration](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_33) | Li-Hsin Cheng | [code](https://github.com/LishinC/VCN) | 77 | | [Contrastive Masked Transformers for Forecasting Renal Transplant Function](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_24) | Leo Milecki | [code](https://github.com/leomlck/renal_transplant_imaging) | 78 | | [Contrastive Re-localization and History Distillation in Federated CMR Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_25) | Xiaoming Qi | [code](https://github.com/JerryQseu/FedCRLD) | 79 | | [Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_9) | Yu Tian | [code](https://github.com/tianyu0207/weakly-polyp) | 80 | | [CRISP - Reliable Uncertainty Estimation for Medical Image Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_47) | Thierry Judge | [code](https://github.com/ThierryJudge/CRISP-uncertainty) | 81 | | [CS2: A Controllable and Simultaneous Synthesizer of Images and Annotations with Minimal Human Intervention](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_1) | Xiaodan Xing | [code](https://github.com/ayanglab/CS2) | 82 | | [D'ARTAGNAN: Counterfactual Video Generation](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_57) | Hadrien Reynaud | [code](https://github.com/dccastro/Morpho-MNIST) | 83 | | [Data-driven Multi-Modal Partial Medical Image Preregistration by Template Space Patch Mapping](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_25) | Ding Xia | [code](https://github.com/ApisXia/PartialMedPreregistration) | 84 | | [Decoupling Predictions in Distributed Learning for Multi-Center Left Atrial MRI Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_49) | Zheyao Gao | [code](https://github.com/key1589745/decouple_predict) | 85 | | [Deep is a Luxury We Don't Have](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_3) | Ahmed Taha | [code](https://github.com/whiterabbit-ai/hct) | 86 | | [Deep Laparoscopic Stereo Matching with Transformers](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_44) | Xuelian Cheng | [code](https://github.com/XuelianCheng/HybridStereoNet-main) | 87 | | [Deep learning-based Head and Neck Radiotherapy Planning Dose Prediction via Beam-wise Dose Decomposition](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_55) | Bin Wang | [code](https://github.com/ukaukaaaa/BeamDosePrediction) | 88 | | [Deep Multimodal Guidance for Medical Image Classification](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_29) | Mayur Mallya | [code](https://github.com/jeremykawahara/derm7pt) | 89 | | [Deep Regression with Spatial-Frequency Feature Coupling and Image Synthesis for Robot-Assisted Endomicroscopy](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_16) | Chi Xu | [code](https://github.com/CVRS-Hamlyn/Deep-Regression-with-SFFC-and-Image-Synthesis-for-Robot-Assisted-Endomicroscopy.git) | 90 | | [Deep-learning Based T1 and T2 Quantification from Undersampled Magnetic Resonance Fingerprinting Data to Track Tracer Kinetics in Small Laboratory Animals](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_41) | Yuning Gu | [code](https://github.com/guyn-idealab/Mouse-MRF-DL/) | 91 | | [DeepMIF: Deep learning based cell profiling for multispectral immunofluorescence images with graphical user interface](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_14) | Yeman Brhane Hagos | [code](https://github.com/YemanBrhane/DeepMIF) | 92 | | [DeepPyramid: Enabling Pyramid View and Deformable Pyramid Reception for Semantic Segmentation in Cataract Surgery Videos](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_27) | Negin Ghamsarian | [code](https://github.com/Negin-Ghamsarian/DeepPyramid_MICCAI2022) | 93 | | [Deformer: Towards Displacement Field Learning for Unsupervised Medical Image Registration](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_14) | Jiashun Chen | [code](https://github.com/CJSOrange/DMR-Deformer) | 94 | | [Degradation-invariant Enhancement of Fundus Images via Pyramid Constraint Network](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_49) | Haofeng Liu | [code](https://github.com/HeverLaw/PCENet-Image-Enhancement) | 95 | | [Denoising of 3D MR images using a voxel-wise hybrid residual MLP-CNN model to improve small lesion diagnostic confidence](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_28) | Haibo Yang | [code](https://github.com/laowangbobo/Residual_MLP_CNN_Mixer) | 96 | | [DeSD: Self-Supervised Learning with Deep Self-Distillation for 3D Medical Image Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_52) | Yiwen Ye | [code](https://github.com/yeerwen/DeSD) | 97 | | [DGMIL: Distribution Guided Multiple Instance Learning for Whole Slide Image Classification](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_3) | Linhao Qu | [code](https://github.com/miccaiif/DGMIL) | 98 | | [Did You Get What You Paid For? Rethinking Annotation Cost of Deep Learning Based Computer Aided Detection in Chest Radiographs](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_25) | Tae Soo Kim | [code](https://github.com/tk-lunit/miccai2022-annotation-cost) | 99 | | [Diffusion Deformable Model for 4D Temporal Medical Image Generation](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_51) | Boah Kim | [code](https://github.com/torchDDM/DDM) | 100 | | [Diffusion Models for Medical Anomaly Detection](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_4) | Julia Wolleb | [code](https://gitlab.com/cian.unibas.ch/diffusion-anomaly) | 101 | | [Digestive Organ Recognition in Video Capsule Endoscopy based on Temporal Segmentation Network](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_14) | Yejee Shin | [code](https://github.com/MAILAB-Yonsei/CE-Organ-Recognition) | 102 | | [Discrepancy and Gradient-guided Multi-Modal Knowledge Distillation for Pathological Glioma Grading](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_61) | Xiaohan Xing | [code](https://github.com/CityU-AIM-Group/MultiModal-learning) | 103 | | [DisQ: Disentangling Quantitative MRI Mapping of the Heart](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_28) | Changchun Yang | [code](https://github.com/Changchun-Yang/DisQ) | 104 | | [Distilling Knowledge from Topological Representations for Pathological Complete Response Prediction](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_6) | Shiyi Du | [code](https://github.com/zoedsy/DK_Topology_PCR) | 105 | | [Domain Adaptive Mitochondria Segmentation via Enforcing Inter-Section Consistency](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_9) | Wei Huang | [code](https://github.com/weih527/DA-ISC) | 106 | | [Domain Specific Convolution and High Frequency Reconstruction based Unsupervised Domain Adaptation for Medical Image Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_62) | Shishuai Hu | [code](https://github.com/ShishuaiHu/DoCR) | 107 | | [Domain-Adaptive 3D Medical Image Synthesis: An Efficient Unsupervised Approach](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_47) | Qingqiao Hu | [code](https://github.com/WinstonHuTiger/2D_VAE_UDA_for_3D_sythesis) | 108 | | [DOMINO: Domain-aware Model Calibration in Medical Image Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_44) | Skylar E. Stolte | [code](https://github.com/lab-smile/DOMINO) | 109 | | [DRGen: Domain Generalization in Diabetic Retinopathy Classification](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_61) | Mohammad Atwany | [code](https://github.com/BioMedIA-MBZUAI/DRGen) | 110 | | [DS3-Net: Difficulty-perceived Common-to-T1ce Semi-Supervised Multimodal MRI Synthesis Network](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_54) | Ziqi Huang | [code](https://github.com/Huangziqi777/DS-3_Net) | 111 | | [DSR: Direct Simultaneous Registration for Multiple 3D Images](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_10) | Zhehua Mao | [code](https://github.com/ZH-Mao/DSR) | 112 | | [Dual-Branch Squeeze-Fusion-Excitation Module for Cross-Modality Registration of Cardiac SPECT and CT](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_5) | Xiongchao Chen | [code](https://github.com/XiongchaoChen/DuSFE_CrossRegistration) | 113 | | [Dual-Distribution Discrepancy for Anomaly Detection in Chest X-Rays](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_56) | Yu Cai | [code](https://github.com/caiyu6666/DDAD) | 114 | | [Dual-graph Learning Convolutional Networks for Interpretable Alzheimer's Disease Diagnosis](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_39) | Tingsong Xiao | [code](https://github.com/xiaotingsong/dGLCN) | 115 | | [Dual-HINet: Dual Hierarchical Integration Network of Multigraphs for Connectional Brain Template Learning](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_29) | Fatih Said Duran | [code](https://github.com/basiralab/Dual-HINet) | 116 | | [DuDoCAF: Dual-Domain Cross-Attention Fusion with Recurrent Transformer for Fast Multi-contrast MR Imaging](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_45) | Jun Lyu | [code](https://github.com/XAIMI-Lab/DuDoCAF) | 117 | | [Dynamic Bank Learning for Semi-supervised Federated Image Diagnosis with Class Imbalance](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_19) | Meirui Jiang | [code](https://github.com/med-air/imFedSemi) | 118 | | [EchoCoTr: Estimation of the Left Ventricular Ejection Fraction from Spatiotemporal Echocardiography](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_36) | Rand Muhtaseb | [code](https://github.com/BioMedIA-MBZUAI/EchoCoTr) | 119 | | [EchoGNN: Explainable Ejection Fraction Estimation with Graph Neural Networks](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_35) | Masoud Mokhtari | [code](https://github.com/MasoudMo/echognn) | 120 | | [Edge-oriented Point-cloud Transformer for 3D Intracranial Aneurysm Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_10) | Yifan Liu | [code](https://github.com/intra3d2019/IntrA) | 121 | | [Embedding Gradient-based Optimization in Image Registration Networks](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_6) | Huaqi Qiu | [code](https://github.com/gradirn/gradirn) | 122 | | [Enhancing model generalization for substantia nigra segmentation using a test-time normalization-based method](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_70) | Tao Hu | [code](https://github.com/MoriLabNU/TTN_for_SN_segmentation) | 123 | | [Estimating Model Performance under Domain Shifts with Class-Specific Confidence Scores](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_66) | Zeju Li | [code](https://github.com/ZerojumpLine/ModelEvaluationUnderClassImbalance) | 124 | | [Evidence fusion with contextual discounting for multi-modality medical image segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_39) | Ling Huang | [code](https://github.com/iWeisskohl/Evidence-fusion-with-contextual-discounting) | 125 | | [Evolutionary Multi-objective Architecture Search Framework: Application to COVID-19 3D CT Classification](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_53) | Xin He | [code](https://github.com/marsggbo/MICCAI2022-EMARS) | 126 | | [Explaining Chest X-ray Pathologies in Natural Language](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_67) | Maxime Kayser | [code](https://github.com/maximek3/MIMIC-NLE) | 127 | | [Exploring Smoothness and Class-Separation for Semi-supervised Medical Image Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_4) | Yicheng Wu | [code](https://github.com/ycwu1997/SS-Net) | 128 | | [Fast FF-to-FFPE Whole Slide Image Translation via Laplacian Pyramid and Contrastive Learning](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_40) | Lei Fan | [code](https://github.com/hellodfan/fastFF2FFPE) | 129 | | [Feature Re-calibration based Multiple Instance Learning for Whole Slide Image Classification](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_41) | Philip Chikontwe | [code](https://github.com/PhilipChicco/FRMIL) | 130 | | [Feature robustness and sex differences in medical imaging: a case study in MRI-based Alzheimer's disease detection](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_9) | Eike Petersen | [code](https://github.com/e-pet/adni-bias) | 131 | | [Federated Stain Normalization for Computational Pathology](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_2) | Nicolas Wagner | [code](https://github.com/MECLabTUDA/BottleGAN) | 132 | | [FedHarmony: Unlearning Scanner Bias with Distributed Data](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_66) | Nicola K. Dinsdale | [code](https://github.com/nkdinsdale/FedHarmony) | 133 | | [Few-shot Generation of Personalized Neural Surrogates for Cardiac Simulation via Bayesian Meta-Learning](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_5) | Xiajun Jiang | [code](https://github.com/john-x-jiang/epnn) | 134 | | [FFCNet: Fourier Transform-Based Frequency Learning and Complex Convolutional Network for Colon Disease Classification](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_8) | Kai-Ni Wang | [code](https://github.com/soleilssss/FFCNet) | 135 | | [fMRI Neurofeedback Learning Patterns are Predictive of Personal and Clinical Traits](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_27) | Rotem Leibovitz | [code](https://github.com/MICCAI22/fmri_nf) | 136 | | [Frequency-Aware Inverse-Consistent Deep Learning for OCT-Angiogram Super-Resolution](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_62) | Weiwen Zhang | [code](https://github.com/KevynUtopia/Frequency-Aware-Inverse-Consistent-OCTA-Super-Resolution) | 137 | | [From Images to Probabilistic Anatomical Shapes: A Deep Variational Bottleneck Approach](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_46) | Jadie Adams | [code](https://github.com/jadie1/VIB-DeepSSM) | 138 | | [FSE Compensated Motion Correction for MRI Using Data Driven Methods](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_67) | Brett Levac | [code](https://github.com/utcsilab/GAN_motion_correction) | 139 | | [FUSSNet: Fusing Two Sources of Uncertainty for Semi-Supervised Medical Image Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_46) | Jinyi Xiang | [code](https://github.com/grant-jpg/FUSSNet) | 140 | | [GaitForeMer: Self-Supervised Pre-Training of Transformers via Human Motion Forecasting for Few-Shot Gait Impairment Severity Estimation](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_13) | Mark Endo | [code](https://github.com/markendo/GaitForeMer) | 141 | | [GazeRadar: A Gaze and Radiomics-guided Disease Localization Framework](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_66) | Moinak Bhattacharya | [code](https://github.com/bmi-imaginelab/gazeradar) | 142 | | [Geometric Constraints for Self-supervised Monocular Depth Estimation on Laparoscopic Images with Dual-task Consistency](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_45) | Wenda Li | [code](https://github.com/MoriLabNU/GCDepthL) | 143 | | [Gigapixel Whole-Slide Images Classification using Locally Supervised Learning](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_19) | Jingwei Zhang | [code](https://github.com/cvlab-stonybrook/local_learning_wsi) | 144 | | [Graph convolutional network with probabilistic spatial regression: application to craniofacial landmark detection from 3D photogrammetry](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_55) | Connor Elkhill | [code](https://github.com/cuMIP/3dphoto) | 145 | | [Graph Emotion Decoding from Visually Evoked Neural Responses](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_38) | Zhongyu Huang | [code](https://github.com/zhongyu1998/GED) | 146 | | [Hand Hygiene Quality Assessment using Image-to-Image Translation](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_7) | Chaofan Wang | [code](https://github.com/chaofanqw/HandTranslation) | 147 | | [Harnessing Deep Bladder Tumor Segmentation with Logical Clinical Knowledge](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_69) | Xiao Huang | [code](https://github.com/huangxiao1234/miccai2022-BTSLCK.git) | 148 | | [Histogram-based unsupervised domain adaptation for medical image classification](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_72) | Pengfei Diao | [code](https://github.com/chronicom/histogram-based-gan-for-lung-disease-classification) | 149 | | [Hybrid Spatio-Temporal Transformer Network for Predicting Ischemic Stroke Lesion Outcomes from 4D CT Perfusion Imaging](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_62) | Kimberly Amador | [code](https://github.com/kimberly-amador/Spatiotemporal-CNN-Transformer) | 150 | | [Identifying and Combating Bias in Segmentation Networks by leveraging multiple resolutions](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_34) | Leonie Henschel | [code](https://github.com/Deep-MI/FastSurfer) | 151 | | [Implicit Neural Representations for Medical Imaging Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_42) | Muhammad Osama Khan | [code](https://github.com/osamakhaan/iosnet) | 152 | | [Improving Trustworthiness of AI Disease Severity Rating in Medical Imaging with Ordinal Conformal Prediction Sets](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_52) | Charles Lu | [code](https://github.com/clu5/lumbar-conformal) | 153 | | [INSightR-Net: Interpretable Neural Network for Regression using Similarity-based Comparisons to Prototypical Examples](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_48) | Linde S. Hesse | [code](https://github.com/lindehesse/INSightR-Net) | 154 | | [InsMix: Towards Realistic Generative Data Augmentation for Nuclei Instance Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_14) | Yi Lin | [code](https://github.com/hust-linyi/insmix) | 155 | | [Interaction-Oriented Feature Decomposition for Medical Image Lesion Detection](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_31) | Junyong Shen | [code](https://github.com/mklz-sjy/IOFD) | 156 | | [Interpretable Graph Neural Networks for Connectome-Based Brain Disorder Analysis](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_36) | Hejie Cui | [code](https://github.com/HennyJie/IBGNN) | 157 | | [Interpretable Modeling and Reduction of Unknown Errors in Mechanistic Operators](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_44) | Maryam Toloubidokhti | [code](https://github.com/miccai2022IMRE/miccai_2022_IMRE) | 158 | | [iSegFormer: Interactive Segmentation via Transformers with Application to 3D Knee MR Images](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_45) | Qin Liu | [code](https://github.com/uncbiag/iSegFormer) | 159 | | [Joint Class-Affinity Loss Correction for Robust Medical Image Segmentation with Noisy Labels](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_56) | Xiaoqing Guo | [code](https://github.com/CityU-AIM-Group/JCAS) | 160 | | [Joint Graph Convolution for Analyzing Brain Structural and Functional Connectome](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_22) | Yueting Li | [code](https://github.com/YuetingLi666/brain_gcn.git) | 161 | | [Joint Prediction of Meningioma Grade and Brain Invasion via Task-Aware Contrastive Learning](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_34) | Tianling Liu | [code](https://github.com/IsDling/predictTCL) | 162 | | [Kernel Attention Transformer (KAT) for Histopathology Whole Slide Image Classification](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_28) | Yushan Zheng | [code](https://github.com/zhengyushan/kat) | 163 | | [Key-frame Guided Network for Thyroid Nodule Recognition using Ultrasound Videos](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_23) | Yuchen Wang | [code](https://github.com/NeuronXJTU/KFGNet) | 164 | | [Landmark-free Statistical Shape Modeling via Neural Flow Deformations](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_44) | David Lüdke | [code](https://github.com/davecasp/flowssm) | 165 | | [Layer Ensembles: A Single-Pass Uncertainty Estimation in Deep Learning for Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_49) | Kaisar Kushibar | [code](https://github.com/pianoza/LayerEnsembles) | 166 | | [Learn to Ignore: Domain Adaptation for Multi-Site MRI Analysis](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_69) | Julia Wolleb | [code](https://gitlab.com/cian.unibas.ch/L2I) | 167 | | [Learning iterative optimisation for deformable image registration of lung CT with recurrent convolutional networks](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_29) | Fenja Falta | [code](https://github.com/multimodallearning/Learn2Optimise/) | 168 | | [Learning shape distributions from large databases of healthy organs: applications to zero-shot and few-shot abnormal pancreas detection](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_45) | Rebeca Vétil | [code](https://github.com/rebeca-vetil/HealthyShapeVAE) | 169 | | [Learning towards Synchronous Network Memorizability and Generalizability for Continual Segmentation across Multiple Sites](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_37) | Jingyang Zhang | [code](https://github.com/jingyzhang/SMG-Learning) | 170 | | [Learning Tumor-Induced Deformations to Improve Tumor-Bearing Brain MR Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_24) | Meng Jia | [code](https://github.com/jiameng1010/Brain_MRI_Tumor) | 171 | | [Learning with Context Encoding for Single-Stage Cranial Bone Labeling and Landmark Localization](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_28) | Jiawei Liu | [code](https://github.com/cuMIP/ctImage) | 172 | | [Lesion Guided Explainable Few Weak-shot Medical Report Generation](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_59) | Jinghan Sun | [code](https://github.com/jinghanSunn/Few-weak-shot-RG) | 173 | | [Lesion-Aware Contrastive Representation Learning for Histopathology Whole Slide Images Analysis](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_27) | Jun Li | [code](https://github.com/junl21/lacl) | 174 | | [Lesion-aware Dynamic Kernel for Polyp Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_10) | Ruifei Zhang | [code](https://github.com/ReaFly/LDNet) | 175 | | [Leveraging Labeling Representations in Uncertainty-based Semi-supervised Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_26) | Sukesh Adiga Vasudeva | [code](https://github.com/adigasu/Labeling_Representations) | 176 | | [LIDP: A Lung Image Dataset with Pathological Information for Lung Cancer Screening](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_74) | Yanbo Shao | [code](https://github.com/MHW-NKU/LIDP-model-evaluation) | 177 | | [LifeLonger: A Benchmark for Continual Disease Classification](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_31) | Mohammad Mahdi Derakhshani | [code](https://github.com/mmderakhshani/LifeLonger) | 178 | | [LiftReg: Limited Angle 2D/3D Deformable Registration](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_20) | Lin Tian | [code](https://github.com/uncbiag/LiftReg) | 179 | | [Light-weight spatio-temporal graphs for segmentation and ejection fraction prediction in cardiac ultrasound](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_37) | Sarina Thomas | [code](https://github.com/guybenyosef/EchoGraphs) | 180 | | [Local Attention Graph-based Transformer for Multi-target Genetic Alteration Prediction](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_37) | Daniel Reisenbüchler | [code](https://github.com/agentdr1/LA_MIL) | 181 | | [Localizing the Recurrent Laryngeal Nerve via Ultrasound with a Bayesian Shape Framework](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_25) | Haoran Dou | [code](https://github.com/wulalago/RLNLocalization) | 182 | | [Longitudinal Infant Functional Connectivity Prediction via Conditional Intensive Triplet Network](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_25) | Xiaowei Yu | [code](https://github.com/Shawey94/Longitudinal-Infant-Functional-Connectivity-Prediction-via-Conditional-Intensive-Triplet-Network) | 183 | | [Long-tailed Multi-label Retinal Diseases Recognition via Relational Learning and Knowledge Distillation](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_68) | Qian Zhou | [code](https://github.com/liyiersan/RLKD) | 184 | | [LSSANet: A Long Short Slice-Aware Network for Pulmonary Nodule Detection](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_63) | Rui Xu | [code](https://github.com/Ruixxxx/LSSANet) | 185 | | [MAL: Multi-modal attention learning for tumor diagnosis based on bipartite graph and multiple branches](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_17) | Menglei Jiao | [code](https://github.com/research-med/MAL) | 186 | | [MaNi: Maximizing Mutual Information for Nuclei Cross-Domain Unsupervised Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_34) | Yash Sharma | [code](https://github.com/YashSharma/MaNi) | 187 | | [MaxStyle: Adversarial Style Composition for Robust Medical Image Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_15) | Chen Chen | [code](https://github.com/cherise215/MaxStyle) | 188 | | [MCP-Net: Inter-frame Motion Correction with Patlak Regularization for Whole-body Dynamic PET](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_16) | Xueqi Guo | [code](https://github.com/gxq1998/MCP-Net) | 189 | | [Measurement-conditioned Denoising Diffusion Probabilistic Model for Under-sampled Medical Image Reconstruction](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_62) | Yutong Xie | [code](https://github.com/Theodore-PKU/MC-DDPM) | 190 | | [Meta-hallucinator: Towards few-shot cross-modality cardiac image segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_13) | Ziyuan Zhao | [code](https://github.com/jacobzhaoziyuan/Meta-Hallucinator) | 191 | | [mmFormer: Multimodal Medical Transformer for Incomplete Multimodal Learning of Brain Tumor Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_11) | Yao Zhang | [code](https://github.com/YaoZhang93/mmFormer) | 192 | | [Modality-adaptive Feature Interaction for Brain Tumor Segmentation with Missing Modalities](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_18) | Zechen Zhao | [code](https://github.com/zzc1909/UNET-MFI) | 193 | | [ModDrop++: A Dynamic Filter Network with Intra-subject Co-training for Multiple Sclerosis Lesion Segmentation with Missing Modalities](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_43) | Han Liu | [code](https://github.com/han-liu/ModDropPlusPlus) | 194 | | [Modelling Cycles in Brain Networks with the Hodge Laplacian](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_31) | Sixtus Dakurah | [code](https://github.com/laplcebeltrami/hodge) | 195 | | [Morphology-Aware Interactive Keypoint Estimation](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_65) | Jinhee Kim | [code](https://github.com/seharanul17/interactive_keypoint_estimation) | 196 | | [Moving from 2D to 3D: volumetric medical image classification for rectal cancer staging](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_75) | Joohyung Lee | [code](https://github.com/JoohyungLee0106/rectal_MR_volume_classification) | 197 | | [mulEEG: A Multi-View Representation Learning on EEG Signals](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_38) | Vamsi Kumar | [code](https://github.com/likith012/mulEEG) | 198 | | [Multidimensional Hypergraph on Delineated Retinal Features for Pathological Myopia Task.](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_53) | Bilha Githinji | [code](https://github.com/qin-lab-tbsi/fundus_choroid_tessellation/) | 199 | | [Multimodal Brain Tumor Segmentation Using Contrastive Learning based Feature Comparison with Monomodal Normal Brain Images](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_12) | Huabing Liu | [code](https://github.com/hbliu98/CLFC-Brain-Tumor-Segmentation) | 200 | | [Multi-Modal Masked Autoencoders for Medical Vision-and-Language Pre-Training](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_65) | Zhihong Chen | [code](https://github.com/zhjohnchan/M3AE) | 201 | | [Multiple Instance Learning with Mixed Supervision in Gleason Grading](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_20) | Hao Bian | [code](https://github.com/bianhao123/mixed_supervision) | 202 | | [Multi-scale Super-resolution Magnetic Resonance Spectroscopic Imaging with Adjustable Sharpness](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_39) | Siyuan Dong | [code](https://github.com/dsy199610/Multiscale-SR-MRSI-adjustable-sharpness) | 203 | | [Multiscale Unsupervised Retinal Edema Area Segmentation in OCT Images](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_64) | Wenguang Yuan | [code](https://github.com/mangoyuan/MUIS) | 204 | | [Multi-TransSP: Multimodal Transformer for Survival Prediction of Nasopharyngeal Carcinoma Patients](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_23) | Hanci Zheng | [code](https://github.com/gluglurice/Multi-TransSP) | 205 | | [NAF: Neural Attenuation Fields for Sparse-View CBCT Reconstruction](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_42) | Ruyi Zha | [code](https://github.com/Ruyi-Zha/naf_cbct) | 206 | | [NestedFormer: Nested Modality-Aware Transformer for Brain Tumor Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_14) | Zhaohu Xing | [code](https://github.com/920232796/NestedFormer) | 207 | | [Neural Annotation Refinement: Development of a New 3D Dataset for Adrenal Gland Analysis](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_48) | Jiancheng Yang | [code](https://github.com/M3DV/NeAR) | 208 | | [Neural Rendering for Stereo 3D Reconstruction of Deformable Tissues in Robotic Surgery](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_41) | Yuehao Wang | [code](https://github.com/med-air/EndoNeRF) | 209 | | [Noise transfer for unsupervised domain adaptation of retinal OCT images](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_67) | Valentin Koch | [code](https://github.com/ValentinKoch/SVDNA) | 210 | | [Non-iterative Coarse-to-fine Registration based on Single-pass Deep Cumulative Learning](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_9) | Mingyuan Meng | [code](https://github.com/MungoMeng/Registration-NICE-Net) | 211 | | [Nonlinear Regression of Remaining Surgical Duration via Bayesian LSTM-based Deep Negative Correlation Learning](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_40) | Junyang Wu | [code](https://github.com/jywu511/BD-Net) | 212 | | [NVUM: Non-Volatile Unbiased Memory for Robust Medical Image Classification](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_52) | Fengbei Liu | [code](https://github.com/FBLADL/NVUM/tree/main/dataset_preparation) | 213 | | [One-Shot Segmentation of Novel White Matter Tracts via Extensive Data Augmentation](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_13) | Wan Liu | [code](https://github.com/liuwan0208/One-Shot-Extensive-Data-Augmentation) | 214 | | [Online Easy Example Mining for Weakly-supervised Gland Segmentation from Histology Images](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_55) | Yi Li | [code](https://github.com/xmed-lab/OEEM) | 215 | | [OnlyCaps-Net, a capsule only based neural network for 2D and 3D semantic segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_33) | Savinien Bonheur | [code](https://github.com/savinienb/OnlyCaps-Net) | 216 | | [Optimal MRI Undersampling Patterns for Pathology Localization](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_73) | Artem Razumov | [code](https://github.com/cviaai/IGS/) | 217 | | [Overlooked Trustworthiness of Saliency Maps](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_43) | Jiajin Zhang | [code](https://github.com/DIAL-RPI/Trustworthiness-of-Medical-XAI) | 218 | | [Patcher: Patch Transformers with Mixture of Experts for Precise Medical Image Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_46) | Yanglan Ou | [code](https://github.com/YanglanOu/patcher.git) | 219 | | [Patch-wise Deep Metric Learning for Unsupervised Low-Dose CT Denoising](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_60) | Chanyong Jung | [code](https://github.com/jcy132/DML_CT) | 220 | | [PD-DWI: Predicting response to neoadjuvant chemotherapy in invasive breast cancer with Physiologically-Decomposed Diffusion-Weighted MRI machine-learning model](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_4) | Maya Gilad | [code](https://github.com/TechnionComputationalMRILab/PD-DWI) | 221 | | [PHTrans: Parallelly Aggregating Global and Local Representations for Medical Image Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_23) | Wentao Liu | [code](https://github.com/lseventeen/PHTrans) | 222 | | [Point Beyond Class: A Benchmark for Weakly Semi-Supervised Abnormality Localization in Chest X-Rays](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_24) | Haoqin Ji | [code](https://github.com/HaozheLiu-ST/Point-Beyond-Class) | 223 | | [Poisson2Sparse: Self-Supervised Poisson Denoising From a Single Image](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_53) | Calvin-Khang Ta | [code](https://github.com/tacalvin/Poisson2Sparse) | 224 | | [Pose-based Tremor Classification for Parkinson's Disease Diagnosis from Video](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_47) | Haozheng Zhang | [code](https://github.com/mattz10966/SPAPNet) | 225 | | [Position-prior Clustering-based Self-attention Module for Knee Cartilage Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_19) | Dong Liang | [code](https://github.com/LeongDong/PCAMNet) | 226 | | [Predicting molecular traits from tissue morphology through self-interactive multi-instance learning](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_13) | Yang Hu | [code](https://github.com/superhy/LCSB-MIL) | 227 | | [Privacy Preserving Image Registration](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_13) | Riccardo Taiello | [code](https://github.com/rtaiello/pp_image_registration) | 228 | | [ProCo: Prototype-aware Contrastive Learning for Long-tailed Medical Image Classification](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_17) | Zhixiong Yang | [code](https://github.com/skyz215/ProCo) | 229 | | [Prognostic Imaging Biomarker Discovery in Survival Analysis for Idiopathic Pulmonary Fibrosis](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_22) | An Zhao | [code](https://github.com/anzhao920/PrognosticBiomarkerDiscovery) | 230 | | [Progression models for imaging data with Longitudinal Variational Auto Encoders](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_1) | Benoît Sauty | [code](https://github.com/bsauty/longitudinal-VAEs) | 231 | | [Progressive Subsampling for Oversampled Data - Application to Quantitative MRI](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_40) | Stefano B. Blumberg | [code](https://github.com/sbb-gh/PROSUB) | 232 | | [Prostate Cancer Histology Synthesis using StyleGAN Latent Space Annotation](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_39) | Gagandeep B. Daroach | [code](https://github.com/NVlabs/stylegan2) | 233 | | [Prototype Learning of Inter-network Connectivity for ASD Diagnosis and Personalized Analysis](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_32) | Eunsong Kang | [code](https://github.com/ku-milab/PL-FC) | 234 | | [Pseudo Bias-Balanced Learning for Debiased Chest X-ray Classification](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_59) | Luyang Luo | [code](https://github.com/LLYXC/PBBL) | 235 | | [RandStainNA: Learning Stain-Agnostic Features from Histology Slides by Bridging Stain Augmentation and Normalization](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_21) | Yiqing Shen | [code](https://github.com/yiqings/RandStainNA) | 236 | | [Real-Time 3D Reconstruction of Human Vocal Folds via High-Speed Laser-Endoscopy](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_1) | Jann-Ole Henningson | [code](https://github.com/Henningson/HLEDataset) | 237 | | [Reducing Positional Variance in Cross-sectional Abdominal CT Slices with Deep Conditional Generative Models](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_20) | Xin Yu | [code](https://github.com/MASILab/C-SliceGen) | 238 | | [Region Proposal Rectification Towards Robust Instance Segmentation of Biological Images](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_13) | Qilong Zhangli | [code](https://github.com/qzhangli/RPR) | 239 | | [Region-guided CycleGANs for Stain Transfer in Whole Slide Images](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_35) | Joseph Boyd | [code](https://github.com/jcboyd/miccai2022-roigan) | 240 | | [Regression Metric Loss: Learning a Semantic Representation Space for Medical Images](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_41) | Hanqing Chao | [code](https://github.com/DIAL-RPI/Regression-Metric-Loss) | 241 | | [Reinforcement learning for active modality selection during diagnosis](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_56) | Gabriel Bernardino | [code](https://github.com/creatis-myriad/featureSelectionRL) | 242 | | [Reliability of quantification estimates in MR Spectroscopy: CNNs vs. traditional model fitting](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_68) | Rudy Rizzo | [code](https://github.com/bellarude/MRS_detasets) | 243 | | [ReMix: A General and Efficient Framework for Multiple Instance Learning based Whole Slide Image Classification](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_4) | Jiawei Yang | [code](https://github.com/TencentAILabHealthcare/ReMix) | 244 | | [Removal of Confounders via Invariant Risk Minimization for Medical Diagnosis](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_55) | Samira Zare | [code](https://github.com/samzare/ConfounderRemoval) | 245 | | [Rethinking Surgical Captioning: End-to-End Window-Based MLP Transformer Using Patches](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_36) | Mengya Xu | [code](https://github.com/XuMengyaAmy/SwinMLP_TranCAP) | 246 | | [Rethinking Surgical Instrument Segmentation: A Background Image Can Be All You Need](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_34) | An Wang | [code](https://github.com/lofrienger/Single_SurgicalScene_For_Segmentation) | 247 | | [Retrieval of surgical phase transitions using reinforcement learning](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_47) | Yitong Zhang | [code](https://github.com/yitongzh/TRN_code) | 248 | | [Rib Suppression in Digital Chest Tomosynthesis](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_66) | Yihua Sun | [code](https://github.com/sunyh1/Rib-Suppression-in-Digital-Chest-Tomosynthesis) | 249 | | [Robust Segmentation of Brain MRI in the Wild with Hierarchical CNNs and no Retraining](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_52) | Benjamin Billot | [code](https://github.com/BBillot/SynthSeg) | 250 | | [RPLHR-CT Dataset and Transformer Baseline for Volumetric Super-Resolution from CT Scans](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_33) | Pengxin Yu | [code](https://github.com/smilenaxx/RPLHR-CT) | 251 | | [S5CL: Unifying Fully-Supervised, Self-Supervised, and Semi-Supervised Learning Through Hierarchical Contrastive Learning](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_10) | Manuel Tran | [code](https://github.com/manuel-tran/s5cl) | 252 | | [Sample hardness based gradient loss for long-tailed cervical cell detection](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_11) | Minmin Liu | [code](https://github.com/M-LLiu/Grad-Libra) | 253 | | [SATr: Slice Attention with Transformer for Universal Lesion Detection](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_16) | Han Li | [code](https://github.com/MIRACLE-Center/A3D_SATr) | 254 | | [Scale-Equivariant Unrolled Neural Networks for Data-Efficient Accelerated MRI Reconstruction](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_70) | Beliz Gunel | [code](https://github.com/ad12/meddlr) | 255 | | [Scribble2D5: Weakly-Supervised Volumetric Image Segmentation via Scribble Annotations](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_23) | Qiuhui Chen | [code](https://github.com/Qybc/Scribble2D5) | 256 | | [Scribble-Supervised Medical Image Segmentation via Dual-Branch Network and Dynamically Mixed Pseudo Labels Supervision](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_50) | Xiangde Luo | [code](https://github.com/HiLab-git/WSL4MIS) | 257 | | [SD-LayerNet: Semi-supervised retinal layer segmentation in OCT using disentangled representation with anatomical priors](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_31) | Botond Fazekas | [code](https://github.com/ABotond/SD-LayerNet) | 258 | | [Segmentation of Whole-brain Tractography: A Deep Learning Algorithm Based on 3D Raw Curve Points](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_18) | Logiraj Kumaralingam | [code](https://github.com/NeuroImageComputingLab/3D_Curve_CNN) | 259 | | [Self-Ensembling Vision Transformer (SEViT) for Robust Medical Image Classification](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_36) | Faris Almalik | [code](https://github.com/faresmalik/SEViT) | 260 | | [Self-supervised 3D anatomy segmentation using self-distilled masked image transformer (SMIT)](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_53) | Jue Jiang | [code](https://github.com/harveerar/SMIT.git) | 261 | | [Self-Supervised Learning of Morphological Representation for 3D EM Segments with Cluster-Instance Correlations](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_10) | Chi Zhang | [code](https://github.com/zhangchih/MorphConNet) | 262 | | [Semi-supervised histological image segmentation via hierarchical consistency enforcement](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_1) | Qiangguo Jin | [code](https://github.com/qgking/HCE) | 263 | | [Semi-supervised learning with data harmonisation for biomarker discovery from resting state fMRI](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_42) | Yi Hao Chan | [code](https://github.com/SCSE-Biomedical-Computing-Group/SHRED) | 264 | | [Semi-Supervised Medical Image Classification with Temporal Knowledge-Aware Regularization](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_12) | Qiushi Yang | [code](https://github.com/CityU-AIM-Group/TEAR) | 265 | | [Semi-Supervised Medical Image Segmentation Using Cross-Model Pseudo-Supervision with Shape Awareness and Local Context Constraints](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_14) | Jinhua Liu | [code](https://github.com/igip-liu/SLC-Net) | 266 | | [Semi-Supervised Spatial Temporal Attention Network for Video Polyp Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_44) | Xinkai Zhao | [code](https://github.com/ShinkaiZ/SSTAN) | 267 | | [Sensor Geometry Generalization to Untrained Conditions in Quantitative Ultrasound Imaging](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_74) | SeokHwan Oh | [code](https://github.com/joseph9337/DSG-net) | 268 | | [SGT: Scene Graph-Guided Transformer for Surgical Report Generation](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_48) | Chen Lin | [code](https://github.com/ccccchenllll/SGT_master) | 269 | | [Shape-Aware Weakly/Semi-Supervised Optic Disc and Cup Segmentation with Regional/Marginal Consistency](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_50) | Yanda Meng | [code](https://github.com/smallmax00/Shape_aware_Weakly-Semi_ODOC_seg) | 270 | | [ShapePU: A New PU Learning Framework Regularized by Global Consistency for Scribble Supervised Cardiac Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_16) | Ke Zhang | [code](https://github.com/BWGZK/CycleMix/tree/main/MSCMR_scribbles) | 271 | | [Show, Attend and Detect: Towards Fine-grained Assessment of Abdominal Aortic Calcification on Vertebral Fracture Assessment Scans](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_42) | Syed Zulqarnain Gilani | [code](https://github.com/NaehaSharif/Show-Attend-and-Detect) | 272 | | [Siamese Encoder-based Spatial-Temporal Mixer for Growth Trend Prediction of Lung Nodules on CT Scans](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_46) | Jiansheng Fang | [code](https://github.com/liaw05/STMixer) | 273 | | [SLAM-TKA: Real-time Intra-operative Measurement of Tibial Resection Plane in Conventional Total Knee Arthroplasty](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_13) | Shuai Zhang | [code](https://github.com/zsustc/Calibration) | 274 | | [Spatial-hierarchical Graph Neural Network with Dynamic Structure Learning for Histological Image Classification](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_18) | Wentai Hou | [code](https://github.com/HeLongHuang/SHGNN) | 275 | | [Stay focused - Enhancing model interpretability through guided feature training](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_12) | Alexander C. Jenke | [code](https://gitlab.com/nct_tso_public/gft) | 276 | | [Stepwise Feature Fusion: Local Guides Global](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_11) | Jinfeng Wang | [code](https://github.com/Qiming-Huang/ssformer) | 277 | | [Stereo Depth Estimation via Self-Supervised Contrastive Representation Learning](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_58) | Samyakh Tukra | [code](https://github.com/CVRS-Hamlyn/Stereo-Depth-Estimation-via-Self-Supervised-Contrastive-Representation-Learning/) | 278 | | [Stroke lesion segmentation from low-quality and few-shot MRIs via similarity-weighted self-ensembling framework](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_9) | Dong Zhang | [code](https://github.com/MINDLAB1/SIGN) | 279 | | [Structure-consistent Restoration Network for Cataract Fundus Image Enhancement](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_47) | Heng Li | [code](https://github.com/liamheng/ArcNet-Medical-Image-Enhancement) | 280 | | [Super-Focus: Domain Adaptation for Embryo Imaging via Self-Supervised Focal Plane Regression](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_70) | Peter He | [code](https://github.com/PeterTheHe/Super-Focus) | 281 | | [SUPER-IVIM-DC: Intra-voxel incoherent motion based Fetal lung maturity assessment from limited DWI data using supervised learning coupled with data-consistency](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_71) | Noam Korngut | [code](https://github.com/TechnionComputationalMRILab/SUPER-IVIM-DC) | 282 | | [Supervised Contrastive Learning to Classify Paranasal Anomalies in the Maxillary Sinus](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_41) | Debayan Bhattacharya | [code](https://github.com/dawnofthedebayan/SupConCE_MICCAI_22) | 283 | | [Supervised Deep Learning for Head Motion Correction in PET](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_19) | Tianyi Zeng | [code](https://github.com/OnofreyLab/dl-hmc_miccai2022) | 284 | | [Suppressing Poisoning Attacks on Federated Learning for Medical Imaging](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_64) | Naif Alkhunaizi | [code](https://github.com/Naiftt/SPAFD) | 285 | | [Surgical-VQA: Visual Question Answering in Surgical Scenes using Transformer](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_4) | Lalithkumar Seenivasan | [code](https://github.com/lalithjets/Surgical_VQA.git) | 286 | | [Survival Prediction of Brain Cancer with Incomplete Radiology, Pathology, Genomic, and Demographic Data](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_60) | Can Cui | [code](https://github.com/mahmoodlab/PathomicFusion/tree/master/data/TCGA_GBMLGG) | 287 | | [SVoRT: Iterative Transformer for Slice-to-Volume Registration in Fetal Brain MRI](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_1) | Junshen Xu | [code](https://github.com/daviddmc/SVoRT) | 288 | | [Swin Deformable Attention U-Net Transformer (SDAUT) for Explainable Fast MRI](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_51) | Jiahao Huang | [code](https://github.com/ayanglab/SDAUT) | 289 | | [Task-oriented Self-supervised Learning for Anomaly Detection in Electroencephalography](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_19) | Yaojia Zheng | [code](https://github.com/ironing/EEG-AD) | 290 | | [Task-relevant Feature Replenishment for Cross-centre Polyp Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_57) | Yutian Shen | [code](https://github.com/CathyS1996/TRFRNet) | 291 | | [TBraTS: Trusted Brain Tumor Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_48) | Ke Zou | [code](https://github.com/Cocofeat/TBraTS) | 292 | | [Test Time Transform Prediction for Open Set Histopathological Image Recognition](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_26) | Adrian Galdran | [code](https://github.com/agaldran/t3po.git) | 293 | | [Test-time Adaptation with Calibration of Medical Image Classification Nets for Label Distribution Shift](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_30) | Wenao Ma | [code](https://github.com/med-air/TTADC) | 294 | | [Test-Time Adaptation with Shape Moments for Image Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_70) | Mathilde Bateson | [code](https://github.com/mathilde-b/TTA) | 295 | | [Test-time image-to-image translation ensembling improves out-of-distribution generalization in histopathology](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_12) | Marin Scalbert | [code](https://gitlab.com/vitadx/articles/test-time-i2i-translation-ensembling) | 296 | | [TGANet: Text-guided attention for improved polyp segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_15) | Nikhil Kumar Tomar | [code](https://github.com/dashishi/LDPolypVideo-Benchmark) | 297 | | [The (de)biasing effect of GAN-based augmentation methods on skin lesion images](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_42) | Agnieszka Mikołajczyk | [code](https://github.com/AgaMiko/debiasing-effect-of-gans) | 298 | | [The Dice loss in the context of missing or empty labels: introducing Φ and ϵ](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_51) | Sofie Tilborghs | [code](https://github.com/JeroenBertels/dicegrad) | 299 | | [The Intrinsic Manifolds of Radiological Images and their Role in Deep Learning](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_65) | Nicholas Konz | [code](https://github.com/mazurowski-lab/radiologyintrinsicmanifolds/) | 300 | | [The Semi-constrained Network-Based Statistic (scNBS): integrating local and global information for brain network inference](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_38) | Wei Dai | [code](https://github.com/daiw3/scNBS.git.) | 301 | | [TINC: Temporally Informed Non-Contrastive Learning for Disease Progression Modeling in Retinal OCT Volumes](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_60) | Taha Emre | [code](https://github.com/EmreTaha/TINC) | 302 | | [TMSS: An End-to-End Transformer-based Multimodal Network for Segmentation and Survival Prediction](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_31) | Numan Saeed | [code](https://github.com/ikboljon/tmss_miccai) | 303 | | [Toward Clinically Assisted Colorectal Polyp Recognition via Structured Cross-modal Representation Consistency](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_14) | Weijie Ma | [code](https://github.com/WeijieMax/CPC-Trans) | 304 | | [Towards Holistic Surgical Scene Understanding](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_42) | Natalia Valderrama | [code](https://github.com/BCV-Uniandes/TAPIR) | 305 | | [Towards Unsupervised Ultrasound Video Clinical Quality Assessment with Multi-Modality Data](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_22) | He Zhao | [code](https://github.com/IBMEOX/UltrasoundVQA) | 306 | | [Tracking by weakly-supervised learning and graph optimization for whole-embryo C. elegans lineages](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_3) | Peter Hirsch | [code](https://github.com/funkelab/linajea) | 307 | | [TransEM: Residual Swin-Transformer based regularized PET image reconstruction](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_18) | Rui Hu | [code](https://github.com/RickHH/TransEM) | 308 | | [Transformer based feature fusion for left ventricle segmentation in 4D flow MRI](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_36) | Xiaowu Sun | [code](https://github.com/xsunn/4DFlowLVSeg) | 309 | | [Transformer based multiple instance learning for weakly supervised histopathology image segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_16) | Ziniu Qian | [code](https://github.com/Nexuslkl/Swin_MIL) | 310 | | [Transformer Based Multi-task Deep Learning with Intravoxel Incoherent Motion Model Fitting for Microvascular Invasion Prediction of Hepatocellular Carcinoma](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_26) | Haoyuan Huang | [code](https://github.com/Ksuriuri/TRMT) | 311 | | [Transformer Lesion Tracker](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_19) | Wen Tang | [code](https://github.com/TangWen920812/TLT) | 312 | | [TranSQ: Transformer-based Semantic Query for Medical Report Generation](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_58) | Ming Kong | [code](https://github.com/zjukongming/TranSQ) | 313 | | [Trichomonas Vaginalis Segmentation in Microscope Images](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_7) | Lin Li | [code](https://github.com/CellRecog/cellRecog) | 314 | | [UASSR:Unsupervised Arbitrary Scale Super-resolution Reconstruction of Single Anisotropic 3D images via Disentangled Representation Learning?](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_43) | Jiale Wang | [code](https://github.com/jialewang1/UASSR) | 315 | | [ULTRA: Uncertainty-aware Label Distribution Learning for Breast Tumor Cellularity Assessment](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_29) | Xiangyu Li | [code](https://github.com/PerceptionComputingLab/ULTRA) | 316 | | [Uncertainty Aware Sampling Framework of Weak-Label Learning for Histology Image Classification](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_36) | Asmaa Aljuhani | [code](https://github.com/machiraju-lab/UA-CNN) | 317 | | [Uncertainty-Guided Lung Nodule Segmentation with Feature-Aware Attention](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_5) | Han Yang | [code](https://github.com/yanghan-yh/UGS-Net) | 318 | | [UNeXt: MLP-based Rapid Medical Image Segmentation Network](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_3) | Jeya Maria Jose Valanarasu | [code](https://github.com/jeya-maria-jose/UNeXt-pytorch) | 319 | | [Uni4Eye: Unified 2D and 3D Self-supervised Pre-training via Masked Image Modeling Transformer for Ophthalmic Image Classification](https://link.springer.com/chapter/10.1007/978-3-031-16452-1_9) | Zhiyuan Cai | [code](https://github.com/Davidczy/Uni4Eye) | 320 | | [Unsupervised Contrastive Learning of Image Representations from Ultrasound Videos with Hard Negative Mining](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_41) | Soumen Basu | [code](https://github.com/983632847/USCL) | 321 | | [Unsupervised Cross-Domain Feature Extraction for Single Blood Cell Image Classification](https://link.springer.com/chapter/10.1007/978-3-031-16437-8_71) | Raheleh Salehi | [code](https://github.com/marrlab/AE-CFE) | 322 | | [Unsupervised Deep Non-Rigid Alignment by Low-Rank Loss and Multi-Input Attention](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_18) | Takanori Asanomi | [code](https://github.com/asanomitakanori/Unsupervised-Deep-Non-Rigid-Alignment-by-Low-Rank-Loss-and-Multi-Input-Attention) | 323 | | [Unsupervised Deformable Image Registration with Absent Correspondences in Pre-operative and Post-Recurrence Brain Tumor MRI Scans](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_3) | Tony C. W. Mok | [code](https://github.com/cwmok/DIRAC) | 324 | | [Unsupervised Nuclei Segmentation using Spatial Organization Priors](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_32) | Loïc Le Bescond | [code](https://github.com/loic-lb/Unsupervised-Nuclei-Segmentation-using-Spatial-Organization-Priors) | 325 | | [Unsupervised Representation Learning of Cingulate Cortical Folding Patterns](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_8) | Joël Chavas | [code](https://github.com/neurospin-projects/2021_jchavas_lguillon_deepcingulate/data) | 326 | | [Usable Region Estimate for Assessing Practical Usability of Medical Image Segmentation Models](https://link.springer.com/chapter/10.1007/978-3-031-16443-9_17) | Yizhe Zhang | [code](https://github.com/yizhezhang2000/ure) | 327 | | [USG-Net: Deep Learning-based Ultrasound Scanning-Guide for an Orthopedic Sonographer](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_3) | Kyungsu Lee | [code](https://github.com/kyungsu-lee-ksl/USG-Net) | 328 | | [Vector Quantisation for Robust Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_63) | Ainkaran Santhirasekaram | [code](https://github.com/AinkaranSanthi/Vector-Quantisation-for-Robust-Segmentation) | 329 | | [Visual deep learning-based explanation for neuritic plaques segmentation in Alzheimer's Disease using weakly annotated whole slide histopathological images](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_33) | Gabriel Jimenez | [code](https://github.com/aramis-lab/miccai2022-stratifiad.git) | 330 | | [Visual explanations for the detection of diabetic retinopathy from retinal fundus images](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_52) | Valentyn Boreiko | [code](https://github.com/valentyn1boreiko/Fundus_VCEs) | 331 | | [vMFNet: Compositionality Meets Domain-generalised Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16449-1_67) | Xiao Liu | [code](https://github.com/vios-s/vMFNet) | 332 | | [Vol2Flow: Segment 3D Volumes using a Sequence of Registration Flows](https://link.springer.com/chapter/10.1007/978-3-031-16440-8_58) | Adeleh Bitarafan | [code](https://github.com/AdelehBitarafan/Vol2Flow) | 333 | | [WavTrans: Synergizing Wavelet and Cross-Attention Transformer for Multi-Contrast MRI Super-resolution](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_44) | Guangyuan Li | [code](https://github.com/XAIMI-Lab/WavTrans) | 334 | | [Weakly Supervised Online Action Detection for Infant General Movements](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_69) | Tongyi Luo | [code](https://github.com/scofiedluo/WO-GMA) | 335 | | [Weakly Supervised Segmentation by Tensor Graph Learning for Whole Slide Images](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_25) | Qinghua Zhang | [code](https://github.com/zqh369/WSNTG) | 336 | | [Weakly-supervised Biomechanically-constrained CT/MRI Registration of the Spine](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_22) | Bailiang Jian | [code](https://github.com/BailiangJ/spine-ct-mr-registration) | 337 | | [What Makes for Automatic Reconstruction of Pulmonary Segments](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_47) | Kaiming Kuang | [code](https://github.com/M3DV/ImPulSe) | 338 | | [Whole Slide Cervical Cancer Screening Using Graph Attention Network and Supervised Contrastive Learning](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_20) | Xin Zhang | [code](https://github.com/ZhangXin1997/MICCAI-2022) | 339 | | [XMorpher: Full Transformer for Deformable Medical Image Registration via Cross Attention](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_21) | Jiacheng Shi | [code](https://github.com/Solemoon/XMorpher) | 340 | | [Y-Net: A Spatiospectral Dual-Encoder Network for Medical Image Segmentation](https://link.springer.com/chapter/10.1007/978-3-031-16434-7_56) | Azade Farshad | 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