nusdbsystem / SSUMML

Semi-Supervised Unpaired Multi-Modal Learning for Label-Efficient Medical Image Segmentation

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SSUMML

Semi-Supervised Unpaired Multi-Modal Learning for Label-Efficient Medical Image Segmentation

by Lei Zhu, Kaiyuan Yang, Meihui Zhang, Ling Ling Chan, Teck Khim Ng and Beng Chin Ooi.

Introduction

This repository contains the implementation of our method for our newly introduced Semi-Supervised Unpaired Multi-Modal Learning, accepted by MICCAI 2021.


Our code will be released soon.

Citation

If this respository is useful for your research, please consider citing:

@inproceedings{zhu2021ssumml,
  title={Semi-Supervised Unpaired Multi-Modal Learning for Label-Efficient Medical Image Segmentation},
  author={Lei Zhu, Kaiyuan Yang, Meihui Zhang, Ling Ling Chan, Teck Khim Ng and Beng Chin Ooi},
  booktitle={MICCAI}, 
  year={2021}
}

Note

  • Please feel free to drop me an email for any question.
  • Contact: Lei Zhu (e0203764@u.nus.edu)

About

Semi-Supervised Unpaired Multi-Modal Learning for Label-Efficient Medical Image Segmentation