[MICCAI2022] This is an official PyTorch implementation for A Robust Volumetric Transformer for Accurate 3D Tumor Segmentation
This repo contains the supported pytorch code and configuration files to reproduce 3D medical image segmentaion results of VT-UNet.
Our previous Code for A Volumetric Transformer for Accurate 3D Tumor Segmentation can be found iside version 1 folder.
Parts of codes are borrowed from nn-UNet.
This software was originally designed and run on a system running Ubuntu.
vi ~/.bashrc
source ~/.bashrc
Create a virtual environment
Install torch
Install other dependencies
cd VTUNet
pip install -e .
cd vtunet
cd /home/VTUNet/DATASET/vtunet_raw/vtunet_raw_data/vtunet_raw_data/Task003_tumor/
This repository makes liberal use of code from open_brats2020, Swin Transformer, Video Swin Transformer, Swin-Unet, nnUNet and nnFormer
@inproceedings{peiris2022robust,
title={A Robust Volumetric Transformer for Accurate 3D Tumor Segmentation},
author={Peiris, Himashi and Hayat, Munawar and Chen, Zhaolin and Egan, Gary and Harandi, Mehrtash},
booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
pages={162--172},
year={2022},
organization={Springer}
}