mmFormer: Multimodal Medical Transformer for Incomplete Multimodal Learning of Brain Tumor Segmentation
Paper
This is the implementation for the paper:
Accepted to MICCAI 2022
Usage.
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Data Preparation
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Download the data from MICCAI 2018 BraTS Challenge.
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Put
Training
folder in./data
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In
./data
, preprocess the data bypython preprocess.py
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Train
- Train the model by
python -m torch.distributed.launch --nproc_per_node=4 --master_port 20003 train.py
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Test
- inference on the test data by
python test
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To inference with missing modalities, please refer to line 201 in
BraTS.py
missing_modal_list.append(MISSING_MODAL)
MISSING_MODAL is a list of missing modalities and each modality is denoted by a number.
0: FLAIR, 1:T1CE, 2:T1, 3:T2