Nightmare4214 / Oneshot_landmark_detection

Official code for "Oneshot Medical Landmark Detection' (MICCAI 2021 early accepted)

oneshot-medical-landmark

Implementation of "One-shot Medical Landmark Detection" -- MICCAI 2021

Paper link: https://arxiv.org/abs/2103.04527

Usage

Environment

python >= 3.5; pytorch >= 1.1.0; torchvision >= 0.6

extra package: tutils

pip install trans-utils

Data Preparation

We train/test our model on Dataset: Cephalometric

We expect the dictionary structure to be the following:

path/to/cephalometric
	400_junior
		001.txt
		...
	400_senior
		001.txt
		...
	RawImage
		TrainingData
			001.bmp
			...
		Test1Data
			151.bmp
			...
		Test2Data
			301.bmp
			...

Training

Stage 1: self-supervised training

python -m scripts.train --tag xxtag

Stage 2: self-training python -m scripts.self_train --tag xxtag

Citation

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={arXiv preprint arXiv:2103.04527},
  year={2021}
}

License

This code is released under the Apache 2.0 license. Please see the LICENSE file for more information

We actively welcome your pull requests!