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[Computers in Biology and Medicine - 2023] This is an official PyTorch implementation for Collaborative networks of Transformers and Convolutional neural networks are powerful and versatile learners for accurate 3D medical image segmentation

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TC-CoNet

This repository contains the supported pytorch code and configuration files to reproduce of TC-CoNet.

TC-CoNet Architecture

Parts of codes are borrowed from nn-UNet. For detailed configuration of the dataset, please refer to nn-UNet.

Environment

Please prepare an environment with Python 3.7, Pytorch 1.7.1, and Windows 10.

Dataset Preparation

Datasets can be acquired via following links:

Dataset I ACDC

Dataset II The Synapse multi-organ CT dataset

Dataset III Brain_tumor

Preprocess Data

  • TCCoNet_convert_decathlon_task -i D:\Codes\Medical_image\UploadGitHub\TCCoNet\DATASET\TCCoNet_raw\TCCoNet_raw_data
  • TCCoNet_plan_and_preprocess -t 2

Functions of scripts

  • 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

Train Model

  • python run_training.py 3d_fullres TCCoNetTrainerV2_TCCoNet_synapse 2 0

Test Model

  • 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

Acknowledgements

This repository makes liberal use of code from Swin Transformer, nnUNet.

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[Computers in Biology and Medicine - 2023] This is an official PyTorch implementation for Collaborative networks of Transformers and Convolutional neural networks are powerful and versatile learners for accurate 3D medical image segmentation

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