R-band-chromosome-recognition

Introduction

This is the code for MICCAI2022 paper "An End-to-End Combinatorial Optimization Method forR-band Chromosome Recognition withGrouping Guided Attention".

Installation

Dependency: Python3; PyTorch

Download the following pretrained model and put them in model/pretrain folder:

https://dl.fbaipublicfiles.com/detr/detr-r50-e632da11.pth

https://download.pytorch.org/models/resnet50-19c8e357.pth

Usage

For training the method proposed in the paper, please running:

python train.py --model resnet50_gfim_dam --model_name model_resnet50_gfim_dam

For training the baseline ResNet50 model, please running:

python train.py --model resnet50 --model_name model_resnet50

Citation

Please cite the following paper if you feel this work is useful to your research

@inproceedings{xia2022end,
  title={An End-to-End Combinatorial Optimization Method for R-band Chromosome Recognition with Grouping Guided Attention},
  author={Xia, Chao and Wang, Jiyue and Qin, Yulei and Gu, Yun and Chen, Bing and Yang, Jie},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={3--13},
  year={2022},
  organization={Springer}
}

Contact

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