Implementation of "One-shot Medical Landmark Detection" -- MICCAI 2021
Paper link: https://doi.org/10.1007/978-3-030-87196-3_17
python >= 3.9
pip install -r req.txt
We up load the four X-ray datasets in google drive, including our proposed BMPLE dataset (Leg X-ray). Please download the files and unzip into the diretory ``dataset''
Stage 1: self-supervised training
python -m scripts_SSL.train --tag xxtag --dataset head
python -m scripts_SSL.SCP --tag xxtag --dataset head
You can set the selected id by SCP and set to config/SSL_{dataset}.yaml and config/TPL_{dataset}.yaml, otherwise you can choose to use the best template.
python -m scripts_SSL.train --tag xxtag --dataset head --finetune 1
Stage 2: self-training
python -m scripts_TPL.train --tag xxtag --dataset head
Please ite our paper if it helps.
@article{yao2021one,
title={One-Shot Medical Landmark Detection},
author={Yao, Qingsong and Quan, Quan and Xiao, Li and Zhou, S Kevin},
journal={Medical Image Computing and Computer Assisted Intervention},
year={2021}
}
This code is released under the Apache 2.0 license. Please see the LICENSE file for more information
We actively welcome your issues!