├── 2DNet ├── ReadME.md ├── data │ └── unzip data.zip here └── src │ ├── dataset │ └── dataset.py │ ├── net │ ├── common.py │ └── models.py │ ├── predict.py │ ├── prepare_data.py │ ├── settings.py │ ├── train.py │ └── tuils │ ├── loss_function.py │ ├── lrs_scheduler.py │ └── tools.py ├── 3DNet ├── README.md ├── datasets │ ├── RSNA19.py │ ├── TReNDs.py │ └── brains18.py ├── images │ ├── efficiency.gif │ └── logo.png ├── model.py ├── models │ └── resnet.py ├── setting.py ├── toy_data │ ├── MRBrainS18 │ │ ├── images │ │ │ └── 070.nii.gz │ │ ├── labels │ │ │ └── 070.nii.gz │ │ └── test_ci.txt │ └── test_ci.txt ├── train_MRBrainS18.py ├── train_RSNA19.py ├── train_TReNDs.py └── util │ ├── file_process.py │ └── logger.py ├── README.md ├── RSNA2019.pdf ├── SequenceModel ├── README.md ├── check_feature.py ├── check_oof.py ├── csv │ ├── train_fold0.csv │ ├── train_fold1.csv │ ├── train_fold2.csv │ ├── train_fold3.csv │ ├── train_fold4.csv │ ├── unzip csv.zip here │ ├── val_fold0.csv │ ├── val_fold1.csv │ ├── val_fold2.csv │ ├── val_fold3.csv │ └── val_fold4.csv ├── features │ └── download stage2_finetune and put it here ├── main.py ├── seq_dataset.py └── settings.py ├── docs ├── overview.png ├── preprocessing.png ├── s1.png └── s2.png └── requirements.txt /2DNet/ReadME.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Scu-sen/1st-RSNA-Intracranial-Hemorrhage-Detection/HEAD/2DNet/ReadME.md -------------------------------------------------------------------------------- /2DNet/data/unzip data.zip here: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /2DNet/src/dataset/dataset.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Scu-sen/1st-RSNA-Intracranial-Hemorrhage-Detection/HEAD/2DNet/src/dataset/dataset.py 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