├── CITATION.cff ├── LICENSE ├── README.md └── VERSION /CITATION.cff: -------------------------------------------------------------------------------- 1 | cff-version: 1.2.0 2 | message: If you use this software, please cite it using these metadata. 3 | title: Table of imaging analysis methods and software 4 | authors: 5 | - family-names: Ahanonu 6 | given-names: Biafra 7 | orcid: https://orcid.org/0000-0002-2021-5848 8 | version: 1.1 9 | date-released: "2018-11-21" 10 | license: MIT 11 | repository-code: https://github.com/bahanonu/imaging_tools -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2018-2021 Biafra Ahanonu 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Imaging analysis tools 2 | A table containing imaging analysis tools for biology and neuroscience, with a focus on calcium imaging. 3 | 4 | Created by Biafra Ahanonu, PhD (HHMI Hanna Gray Fellow, Basbaum Lab, UCSF). 5 | 6 | [![DOI](https://zenodo.org/badge/427113554.svg)](https://zenodo.org/badge/latestdoi/427113554) 7 | 8 | 9 |

10 | 11 | ciapkgMovie 12 | 13 |

Calcium imaging analysis with CIAtah (https://github.com/bahanonu/ciatah). 14 |

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16 | 17 | The table can also be found at: 18 | - https://bahanonu.com/brain/imaging_tools/ 19 | - https://bahanonu.com/syscarut/articles/233/ 20 | - If you would like to cite this table, see `Cite this repository` in the right `About` section or https://zenodo.org/record/8349533. 21 | 22 | _Notes_: 23 | - I use _cell extraction_ to refer to algorithms that perform cell segmentation and extract neural activity traces. 24 | - In cases where the publication did not explicitly give the algorithm a name, made one based on the underlying method used. 25 | - This table includes algorithms that simultaneously extract cell images/contours and reconstruct cell activity traces along with ones mainly focused on determining one or the other. 26 | - Several calcium imaging related packages have also been included along with algorithms dealing with post-hoc handling of data or cell activity traces. 27 | - Future versions of the repository will include table file (e.g. CSV) and basic LaTeX code so others can import or modify the table more easily going forward. 28 | - Depending on monitor size and browser, scroll horizontally to see right-most table columns (e.g. websites/URLs). 29 | - Any additional papers or algorithms that should be added or suggested updates to the table, leave a comment on the associated blog post or open an issue on the GitHub page, I want to make sure everyone’s brilliant work is acknowledged! 30 | 31 | 32 |
Table 1:Ca2+ imaging cell extraction and trace reconstruction algorithms
 35 | 36 | 37 | 38 |
53 | 64 | 76 | 86 | 100 | 116 | 126 | 138 | 150 | 160 | 171 | 183 | 193 | 205 | 215 | 227 | 239 | 251 | 263 | 275 | 285 | 297 | 310 | 320 | 343 | 355 | 369 | 379 | 391 | 403 | 415 | 427 | 438 | 458 | 470 | 482 | 494 | 504 | 516 | 528 | 540 | 552 | 565 | 577 | 587 | 599 | 609 | 619 | 629 | 641 | 653 | 670 | 680 | 690 | 700 | 710 | 722 | 732 | 744 | 754 | 764 | 776 | 788 | 800 | 813 | 825 | 837 | 851 | 863 | 875 | 887 | 897 | 909 | 921 | 933 | 945 | 957 | 969 | 981 | 993 | 1005 | 1017 | 1029 | 1041 | 1053 | 1065 | 1077 | 1089 | 1102 | 1114 | 1126 | 1138 | 1148 | 1160 | 1173 | 1185 | 1197 | 1209 | 1221 | 1233 | 1245 | 1257 | 1269 | 1281 | 1293 | 1305 | 1317 | 1327 | 1339 | 1351 | 1363 | 1375 | 1387 | 1399 | 1412 |
# Method YearAnalysis pipeline Notes/Code Citation
1 PhaseCorrelation 1996Motion correction. •  Phase correlation for motion correction, to include translation, rotation, and scale-invariance. Reddy and Chatterji 1996
2 Turboreg 1998Motion correction. •  Motion correction.
•  http://bigwww.epfl.ch/thevenaz/turboreg/ 		Thevenaz et al. 1998
3 subPixelPhase 2002Motion correction. •  Closed-form solution to subpixel translation estimation using phase correlation. Foroosh et al. 2002
4 ROI 2005Cell extraction •  Matrix multiplication; in some methods neuropil/background subtraction implemented. Kerr et al. 2005; Kuchibhotla et al. 2014; Peron et al. 2015
5 CellProfiler 2006Cell segmentation •  Multi-algorithm pipeline for cell segmentation.
•  https://cellprofiler.org 		Carpenter et al. 2006; McQuin et al. 2018; Lamprecht et al. 2007
6 PCA-ICA 2009Cell extraction •  Cell extraction using principal component analysis (PCA) followed by independent component analysis (ICA). Mukamel et al. 2009
7 ANTs 2009Image analysis •  Suite of tools for registering and analyzing imaging data.
•  http://stnava.github.io/ANTs/ 		Avants et al. 2009
8 elastix 2009Motion correction •  A general toolbox for rigid and non-rigid image registration.
•  https://elastix.lumc.nl 		Klein et al. 2009
9 Lucas–Kanade framework2009Motion correction •  Lucas-Kanade framework for non-uniform motion image registration. Greenberg and Kerr 2009
10 CIRF (calcium-behavior) 2011Cell extraction •  Regressive model to obtain Ca2+ signal based on behavior. Miri et al. 2011
11 openBIS 2011Data handling •  FAIR data management.
•  https://openbis.ch 		Bauch et al. 2011
12 Automated ROI analysis 2012Cell extraction •  Automatic ellipses based ROI detection. Francis et al. 2012
13 OMERO 2012Data handling •  Microscopy data handling.
•  https://www.openmicroscopy.org 		Allan et al. 2012
14 ADINA 2013Cell extraction •  Sparse dictionary learning. Diego et al. 2013
15 TPP 2013Analysis pipeline •  Tool for processing two-photon calcium imaging data, e.g. finding cells with SeNeCA.
•  http://uemweb.biomed.cas.cz/tpp/ 		Tomek et al. 2013
16 NMF 2014Cell extraction •  Cell extraction using nonnegative matrix factorization (NMF). Followed by CNMF. Pnevmatikakis et al. 2014; Maruyama et al. 2014
17 SIMA 2014Analysis pipeline •  Normalized cut segmentation, motion correction, etc.
•  https://github.com/losonczylab/sima 		Kaifosh et al. 2014
18 DataJoint 2015Data handling •  Schema for data handling.
•  https://github.com/datajoint/datajoint-matlab 		Yatsenko et al. 2015
19 NWB 2015Data handling •  Neurodata Without Borders (NWB) initiative to produce a common data format for electrophysiology and imaging studies.
•  https://github.com/NeurodataWithoutBorders 		Teeters et al. 2015
20 Suite2p 2016Cell extraction •  Generative model along with GUIs. Pachitariu et al. 2016
21 CNMF (CaImAn) 2016Cell extraction •  Constrained NMF (CNMF).
•  https://github.com/flatironinstitute/CaImAn-MATLAB 		Pnevmatikakis et al. 2016
22 CNMF-E 2016Cell extraction •  CNMF + background model to handle one-photon data.
•  https://github.com/zhoupc/CNMF_E 		Zhou et al. 2016, 2018
23 Apthorpe CNN 2016Cell segmentation •  Convolutional neural network (CNN). Apthorpe et al. 2016
24 moco 2016Motion correction •  Fourier-transform based motion correction.
•  https://github.com/NTCColumbia/moco 		Dubbs et al. 2016
25 Cytomine 2016Analysis GUI •  Analysis of large-scale imaging data.
•  https://cytomine.be 		Marée et al. 2016
26 ROI clustering 2016Cell extraction •  Select high-intensity pixels then perform clustering to segment.
•  https://www.bu.edu/hanlab/files/2016/02/pfgc.zip 		Mohammed et al. 2016
27 CELLMax (conference) 2017Cell extraction •  Cell segmentation and activity trace extraction using a maximum likelihood approach. Ahanonu et al. 2018, 2017; Ahanonu 2018
28 sc-CNMF 2017Cell extraction •  CNMF + GMM/RNN seed cleansing. Lu et al. 2017
29 OASIS 2017Trace analysis •  Generalized pool adjacent violators algorithm.
•  https://github.com/zhoupc/OASIS_matlab 		Friedrich et al. 2017
30 ABLE 2017Cell segmentation •  Multiple active contours and a cost function to identify cells in 2P data.
•  https://github.com/StephanieRey/ABLE 		Reynolds et al. 2017
31 SCALPEL 2017Cell extraction •  Dictionary learning, dissimilarity, and clustering.
•  https://cran.r-project.org/web/packages/scalpel/index.html 		Petersen et al. 2017
32 HNCcorr 2017Cell segmentation •  Combinatorial optimization (correlation space analysis).
•  https://github.com/hochbaumGroup/HNCcorr 		Spaen et al. 2017
33 OnACID 2017Cell extraction (online) •  NMF variant for online Ca2+ imaging processing. Giovannucci et al. 2017
34 EXTRACT 2017Cell extraction •  Robust statistical estimation. Inan et al. 2017
35 NETCAL 2017Analysis pipeline •  Calcium imaging analysis GUI.
•  https://github.com/orlandi/netcal 		Orlandi et al.
36 NoRMCorre 2017Motion correction. •  Piecewise rigid motion correction.
•  https://github.com/simonsfoundation/NoRMCorre 		Pnevmatikakis and Giovannucci 2017
37 CellReg 2017Cross-session alignment•  Alignment of cells across days using a probabilistic approach.
•  https://github.com/zivlab/CellReg 		Sheintuch et al. 2017
38 NeuroSeg 2017Cell segmentation •  Filtering and seed/clustering based cell segmentation.
•  https://github.com/baidatong/NeuroSeg 		Guan et al. 2018
39 CNMF-E+ 2017Cell extraction •  Shrinkage estimation to improve CNMF-E initialization. Takekawa et al. 2017
40 Toolbox-Romano 2017Analysis pipeline •  Full analysis pipeline with ROI-based segmentation
•  https://github.com/zebrain-lab/Toolbox-Romano-et-al 		Romano et al. 2017
41 SamuROI 2017Analysis GUI •  GUI for data visualization
•  https://github.com/samuroi/SamuROI 		Rueckl et al. 2017
42 KNIME 2017Analysis pipeline •  Workflow manager for data analysis.
•  https://www.knime.com 		Fillbrunn et al. 2017
43 U-Net2DS 2017Cell segmentation •  Evaluated several deep learning models on Neurofinder, U-Net2DS best.
•  https://github.com/alexklibisz/deep-calcium 		Klibisz et al. 2017
44 CLEAN (conference) 2018Cell sorting •  Machine learning based cell sorting of cell extraction outputs based on image and activity trace features. Ahanonu et al. 2018; Ahanonu 2018
45 FISSA 2018Trace analysis •  Neuropil decontamination using local region around cell.
•  https://github.com/rochefort-lab/fissa 		Keemink et al. 2018
46 LSSC 2018Cell segmentation •  Spectral clustering; variant to find local subset of eigenvectors. Mishne et al. 2018
47 PMD - PCA 2018Denoising •  Spatially-localized penalized matrix decomposition for denoising; compression; and improved demixing.
•  https://github.com/paninski-lab/funimag 		Buchanan et al. 2018
48 MIN1PIPE 2018Analysis pipeline •  Pre-processing to enhance neural signals then sc-CNMF for cell extraction. Lu et al. 2018
49 CaImAn (preprint) 2018Analysis pipeline •  CNMF + several other processing tools. Giovannucci et al. 2018
50 SEUDO (preprint) 2018Trace analysis •  Mixture of Gaussians + maximum likelihood; post-hoc activity trace correction. Gauthier et al. 2018
51 ACSAT 2018Cell segmentation •  Global and local adaptive thresholding to identify neurons.
•  https://github.com/sshen8/acsat 		Shen et al. 2018
52 onlineMotionCorrection 2018Motion correction •  Tested multiple algorithms and developed an online motion correction pipeline.
•  https://github.com/amitani/onlineMotionCorrection 		Mitani and Komiyama 2018
53 CIAtah 2019Analysis pipeline •  1P and 2P Imaging analysis pipeline supporting PCA-ICA, CNMF, CELLMax, EXTRACT, etc.
•  https://github.com/bahanonu/ciatah 		Corder et al. 2019; Ahanonu 2018; Ahanonu and Corder 2022
54 NAOMi (bioRxiv) 2019Simulator •  Generative model for creating simulated calcium imaging movies. Charles et al. 2019
55 CALIMA 2019Analysis pipeline •  Calcium imaging analysis GUI. Radstake et al. 2019
56 STNeuroNet 2019Cell segmentation •  Convolutional neural network to detect and segment cells. Soltanian-Zadeh et al. 2019
57 AQuA 2019Cell extraction •  Astrocyte imaging focused. Non-ROI cluster and propagation based detection of events. Wang et al. 2019
58 CaImAn 2019Analysis pipeline •  Popular calcium imaging pipeline that includes CNMF + several other processing tools.
•  https://github.com/flatironinstitute/CaImAn 		Giovannucci et al. 2019
59 DL+RWL1-SF 2019Cell extraction •  Dictionary learning and spatial correlation based cell extraction. Mishne and Charles 2019
60 Segment2P 2019Cell segmentation •  Pre-process images and run through DeepLabV3.
•  https://github.com/NoahDolev/Segment2P 		Dolev et al. 2019
61 LANMC 2019Motion correction •  Long short-term memory non-rigid motion correction, reduce computational cost by predicting non-rigid motion. Chen et al. 2019
62 marked point processes 2020Cell extraction •  Probabilistic generative model, specifically a marked point process, to extract activity traces. Shibue and Komaki 2020
63 LocaNMF 2020Region extraction •  Localized semi-nonnegative matrix factorization for extracting active regions.
•  https://github.com/ikinsella/locaNMF 		Saxena et al. 2020
64 EZcalcium 2020Analysis pipeline •  Calcium imaging analysis toolbox.
•  https://github.com/porteralab/EZcalcium 		Cantu et al. 2020
65 OnACID-E + ring CNN 2020Cell extraction (online) •  OnACID for miniscope and new ring CNN background model to improve accuracy.
•  https://github.com/flatironinstitute/CaImAn 		Friedrich et al. 2020
66 Auto CNMF-E sorting 2020Cell sorting •  Machine learning (AutoML) based curation of CNMF-E outputs.
•  https://github.com/jf-lab/cnmfe-reviewer 		Tran et al. 2020a,b
67 DeepInterpolation 2020Denoising •  Encoder-decoder architecture with 2D conv. to denoise imaging data.
•  https://github.com/AllenInstitute/deepinterpolation 		Lecoq et al. 2020
68 BIAFLOWS 2020Benchmarking •  Framework for benchmarking imaging analysis workflows.
•  https://biaflows.neubias.org 		Rubens et al. 2020
69 FIBSI 2020Trace analysis •  Extension of Ramer-Douglas-Peucker algorithm to identify baseline that is used for signal detection.
•  https://github.com/rmcassidy/FIBSI_program 		Cassidy et al. 2020; Alles et al. 2021
70 DISCo 2020Cell segmentation •  Pixel correlation and deep learning (CNN) + graph based segmentation.
•  https://github.com/EKirschbaum/DISCo 		Kirschbaum et al. 2020
71 DeepCINAC 2020Trace analysis •  Trace analysis after human labeling followed by CNNs + bidirectional long-short term memory (LSTM) network.
•  https://gitlab.com/cossartlab/deepcinac 		Denis et al. 2020
72 NDSEP 2020Cell extraction •  Dataflow framework for real-time calcium imaging processing.
•  http://dspcad-www.iacs.umd.edu/bcnm/index.html 		Lee et al. 2020
73 DeepBrainSeg 2020Segmentation •  Dual-pathway CNN to learn local and contextual features. Tan et al. 2020
74 RT-3DMC 2020Motion correction •  Bead or soma tracking for real-time motion correction during 2P imaging.
•  https://github.com/SilverLabUCL/SilverLab-Microscope 		Griffiths et al. 2020
75 Cellpose 2021Cell segmentation •  Neural network and gradient-based cell segmentation.
•  https://github.com/mouseland/cellpose 		Stringer et al. 2021
76 NAOMi 2021Simulator •  Detailed model simulation for benchmarking calcium imaging algorithms.
•  https://bitbucket.org/adamshch/naomi_sim/src/master/ 		Song et al. 2021
77 OnACID-E + ring CNN 2021Cell extraction (online) •  OnACID for 1P data and ring CNN background model.
•  https://github.com/flatironinstitute/CaImAn 		Friedrich et al. 2021
78 EXTRACT 2021Cell extraction •  Robust statistics based cell extraction.
•  https://github.com/schnitzer-lab/EXTRACT-public 		Inan et al. 2021
79 Minian 2021Analysis pipeline •  Imaging analysis pipeline with CNMF for cell extraction, in part using Jupyter notebooks with GUI elements.
•  https://github.com/DeniseCaiLab/minian 		Dong et al. 2021
80 Mesmerize 2021Analysis pipeline •  Imaging analysis platform with CaImAn for cell extraction, import support for other cell extraction algorithms.
•  https://github.com/kushalkolar/MESmerize 		Kolar et al. 2021
81 DeepInterpolation 2021Denoising •  Encoder-decoder architecture with 2D conv. to denoise imaging data.
•  https://github.com/AllenInstitute/deepinterpolation 		Lecoq et al. 2021
82 BEAR 2021Cell extraction •  Neural network approximation of PCA for cell extraction.
•  https://github.com/NICALab/BEAR 		Han et al. 2021
83 CaPTure 2021Cell extraction •  ROI segmentation and activity extraction.
•  https://github.com/LieberInstitute/CaPTure 		Tippani et al. 2021
84 CASCADE 2021Trace analysis •  Spike inference based on dual ephys/calcium imaging recordings.
•  https://github.com/HelmchenLabSoftware/Cascade 		Rupprecht et al. 2021
85 VolPy 2021Analysis pipeline •  Voltage imaging analysis pipeline integrated into CaImAn.
•  https://github.com/flatironinstitute/CaImAn 		Cai et al. 2021
86 DeepCAD 2021Denoising •  Deep neural network based denoising.
•  https://github.com/cabooster/DeepCAD-RT 		Li et al. 2021
87 SpecSeg 2021Cell extraction •  Spectral density of pixels to identify ROIs. Also incorporates motion correction and cross-session matching.
•  https://github.com/Leveltlab/SpectralSegmentation 		de Kraker et al. 2021
88 FIOLA 2021Cell extraction (online) •  GPU- and computational graph-based speed-ups along with non-negative least squares for post-initialization signal extraction.
•  https://github.com/nel-lab/FIOLA 		Giovannucci et al. 2021
89 PatchWarp 2021Motion correction •  Affine transformation of subfields followed by stitching subfields together.
•  https://github.com/ryhattori/PatchWarp 		Hattori and Komiyama 2021
90 MVG-CNN 2021Region extraction •  Automated sleep states classification using multiplex visibility graphs and deep learning. Data URL.
•  https://github.com/comp-imaging-sci/MVG-CNN 		Zhang et al. 2021
91 Flow-Registration 2021Motion correction •  Variational optical flow for non-uniform motion correction
•  https://github.com/phflot/flow_registration 		Flotho et al. 2022
92 SUNS 2021Cell segmentation •  Cell segmentation using shallow U-Nets.
•  https://github.com/YijunBao/Shallow-UNet-Neuron-Segmentation_SUNS 		Bao et al. 2021
93 Carignan 2021Cell extraction •  Online cell extraction and triggering based on OnACID and CaImAn.
•  https://github.com/tzklab/carignan 		Taniguchi et al. 2021
94 MullenClassifier 2021Cell sorting •  Feature extraction from cell images and tracs followed by supervised learning classifier. Mullen et al. 2021
95 timeUnet 2021Denoising •  Deep learning for denoising with temporal information added in.
•  https://github.com/BoHuangLab/Transfer-Learning-Denoising/ 		Wang et al. 2021
96 EMC2 2021Motion correction •  Wavelet decomposition to detect bright spots followed by motion correction with multiple hypothesis tracking and computing elastic deformation.
•  https://icy.bioimageanalysis.org/plugin/elastic-motion-correction-concatenation-emc2-of-tracks/ 		Lagache et al. 2021
97 GraFT 2022Cell extraction •  Dictionary-based learning of activity traces followed by graph-based segmentation.
•  https://github.com/adamshch/GraFT-analysis 		Charles et al. 2022
98 CaPTure 2022Analysis pipeline •  Binary/watershed segmentation followed by ROI-based mean traces.
•  https://github.com/LieberInstitute/CaPTure 		Tippani et al. 2022
99 SpecSeg 2022Cell segmentation •  Cross spectral power-based segmentation of neurons and neurites.
•  https://github.com/Leveltlab/SpectralSegmentation 		de Kraker et al. 2022
100CITE-On 2022Cell extraction •  Online cell detection and trace extraction using CNNs.
•  https://gitlab.iit.it/fellin-public/cite-on 		Sità et al. 2022
101DL-assisted 2P fiberscope2022Denoising •  Denoising 2P fiberscope data using deep neural network (conditional generative adversarial network).
•  https://figshare.com/articles/dataset/Data/19193792 		Guan et al. 2022
1024SM 2022Cell extraction •  Generative adversarial network for image segmentation.
•  https://github.com/SharifAmit/4SM 		Kamran et al. 2022
103DeepCAD-RT 2022Denoising •  Improved version of DeepCAD for real time performance.
•  https://github.com/cabooster/DeepCAD-RT/ 		Li et al. 2023a
104SEUDO 2022Trace analysis •  Mixture of Gaussians + maximum likelihood; post-hoc activity trace correction.
•  https://github.com/adamshch/SEUDO 		Gauthier et al. 2022
105AxialMotionCorrect 2022Motion correction •  Axial motion correction via multi-plane scanning plus maximum likelihood optimization.
•  https://gitlab.com/anflores/axial_motion_correction 		Flores-Valle and Seelig 2022
106FIFER 2022Motion correction •  Feature-based motion correction, finding features using a density-based estimating and clustering algorithm and matching features with a similarity metric for registration.
•  https://github.com/Weiyi-Liu-Unique/FIFER		Liu et al. 2022
107NWB 2022Data handling •  Neurodata Without Borders (NWB) to standardize ephys and imaging data across tools.
•  https://github.com/NeurodataWithoutBorders 		Rübel et al. 2022
108DeCalciOn 2023Online analysis pipeline•  Integrate hardware and software to online decode calcium signals.
•  https://github.com/zhe-ch/ACTEV 		Chen et al. 2023
109jGCaMP8 2023Calcium indicator •  Improved calcium indicators with increased sensitivity and reduced background. Zhang et al. 2023a
110NeuroSeg-II 2023Cell segmentation •  2P cell segmentation using region-based convolutional neural network with modifications.
•  https://github.com/XZH-James/NeuroSeg2 		Xu et al. 2023
111CaliAli 2023Cross-session alignment•  Cross-session alignment using vasculature information.
•  https://github.com/CaliAli-PV/CaliAli 		Vergara et al. 2023
112DeepWonder 2023Cell extraction •  Deep-learning-based cell finding for widefield datasets.
•  https://github.com/yuanlong-o/Deep_widefield_cal_inferece 		Zhang et al. 2023b
113ASTRA 2023Cell segmentation •  Deep neural network for astrocyte segmentation.
•  https://gitlab.iit.it/fellin-public/astra 		Bonato et al. 2023
114SRDTrans 2023Denoise •  Spatial redundancy for training followed by spatiotemporal transformer architecture to reduce CNN bias/issues.
•  https://github.com/cabooster/SRDTrans 		Li et al. 2023b
115REALS 2023Motion correction •  Motion correction via simultaneous transformation and low rank and sparse decomposition with gradient-based updates.
•  https://openaccess.thecvf.com/content/WACV2023/supplemental/Cho_Robust_and_Efficient_WACV_2023_supplemental.zip 		Cho et al. 2023
116LD-MCM 2023Motion correction •  Motion correction using deep learning feature identification and control point registration.
•  https://github.com/bahanonu/ciatah 		Ahanonu et al. 2023
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2552 |

Footnotes

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