CityU-AIM-Group / JCAS

[MICCAI'22] Joint Class-Affinity Loss Correction for Robust Medical Image Segmentation with Noisy Labels

Joint Class-Affinity Loss Correction for Robust Medical Image Segmentation with Noisy Labels

by Xiaoqing Guo.

Summary:

Intoduction:

This repository is for our MICCAI 2022 paper "Joint Class-Affinity Loss Correction for Robust Medical Image Segmentation with Noisy Labels"

Framework:

Usage:

Requirement:

Pytorch 1.3 & Pytorch 1.7 are ok

Python 3.6

Preprocessing:

Clone the repository:

git clone https://github.com/Guo-Xiaoqing/JCAS.git
cd SimT 
bash sh_train_pre.sh ## Generate class distribution npy
bash sh_train_s1.sh ## Stage of warmup
bash sh_train_s2.sh ## Stage of training with JCAS

Citation:

@inproceedings{guo2022joint,
  title={Joint Class-Affinity Loss Correction for Robust Medical Image Segmentation with Noisy Labels},
  author={Guo, Xiaoqing and Yuan, Yixuan},
  booktitle= {MICCAI},
  year={2022}
}

Questions:

Please contact "[e-mail]"