This repository contains the supported pytorch code and configuration files to reproduce of TC-CoNet.
Parts of codes are borrowed from nn-UNet. For detailed configuration of the dataset, please refer to nn-UNet.
Please prepare an environment with Python 3.7, Pytorch 1.7.1, and Windows 10.
Datasets can be acquired via following links:
Dataset I ACDC
Dataset II The Synapse multi-organ CT dataset
Dataset III Brain_tumor
- TCCoNet_convert_decathlon_task -i D:\Codes\Medical_image\UploadGitHub\TCCoNet\DATASET\TCCoNet_raw\TCCoNet_raw_data
- TCCoNet_plan_and_preprocess -t 2
- Network architecture:
TCCoNet\TCCoNet\network_architecture\TCCoNet_acdc.py
TCCoNet\TCCoNet\network_architecture\TCCoNet_synapse.py
TCCoNet\TCCoNet\network_architecture\TCCoNet_tumor.py
TCCoNet\TCCoNet\network_architecture\TCCoNet_heart.py
TCCoNet\TCCoNet\network_architecture\TCCoNet_lung.py
- Trainer for dataset:
TCCoNet\TCCoNet\training\network_training\TCCoNetTrainerV2_TCCoNet_acdc.py
TCCoNet\TCCoNet\training\network_training\TCCoNetTrainerV2_TCCoNet_synapse.py
TCCoNet\TCCoNet\training\network_training\TCCoNetTrainerV2_TCCoNet_tumor.py
TCCoNet\TCCoNet\training\network_training\TCCoNetTrainerV2_TCCoNet_heart.py
TCCoNet\TCCoNet\training\network_training\TCCoNetTrainerV2_TCCoNet_lung.py
- python run_training.py 3d_fullres TCCoNetTrainerV2_TCCoNet_synapse 2 0
-
python predict.py -i D:\Codes\Medical_image\UploadGitHub\TCCoNet\DATASET\TCCoNet_raw\TCCoNet_raw_data\Task002_Synapse\imagesTs -o D:\Codes\Medical_image\UploadGitHub\TCCoNet\DATASET\TCCoNet_raw\TCCoNet_raw_data\Task002_Synapse\imagesTs_infer -m D:\Codes\Medical_image\UploadGitHub\TCCoNet\DATASET\TCCoNet_trained_models\TCCoNet\3d_fullres\Task002_Synapse\TCCoNetTrainerV2_TCCoNet_synapse__TCCoNetPlansv2.1 -f 0
-
python TCCoNet/inference_synapse.py
This repository makes liberal use of code from Swin Transformer, nnUNet.