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TriMix: A General Framework for Medical Image Segmentation from Limited Supervision
Introduction
This repository provides PyTorch implementation of our ACCV2022 paper 'TriMix: A General Framework for Medical Image Segmentation from Limited Supervision'.
<p align="center"> <img src="./TriMix.png" width="60%"> </p>Usage
[1]. Prepare the dataset
Please follow Luo et al. to prepare the ACDC dataset and put it in <u>./TriMix/semi_supervised/2D/dataset</u> and <u>./TriMix/scribble_supervised/ACDC/dataset</u>
Please follow CycleMix to prepare the MSCMRSeg dataset and put it in <u>./TriMix/scribble_supervised/MSCMR/dataset</u>
Please follow UA-MT to prepare the LA dataset and put it in <u>./TriMix/semi_supervised/3D/dataset</u>
[2]. Train and test the model:
python train_trimix.py
python test_trimix.py
Acknowledgement
Benchmarks on ACDC, MSCMRSeg, and LA datasets in this repository borrow part of codes from Luo et al., CycleMix, and UA-MT implementations. We also appreciate other public codebases cited in our paper.
Note
Contact: Zhou Zheng (zzheng@mori.m.is.nagoya-u.ac.jp)