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label-augmentation

https://github.com/vine-lab-vu/label-augmentation

Science Score: 54.0%

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    Scientific vocabulary similarity
    Low similarity (10.0%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: vine-lab-vu
  • Language: Python
  • Default Branch: main
  • Size: 124 KB
Statistics
  • Stars: 2
  • Watchers: 1
  • Forks: 1
  • Open Issues: 0
  • Releases: 0
Created over 2 years ago · Last pushed 11 months ago
Metadata Files
Readme Citation

README.md

Label Augmentation Method for Medical Landmark Detection

Important Notification

This repository will not be updated anymore. Please go to the repository below for future updates. Thank you. - https://github.com/yehyunsuh/Anatomical-Landmark-Detector-Training

Project Information

Label augmentation method for medical landmark detection in hip radiograph images
Yehyun Suh, Peter Chan, J. Ryan Martin, and Daniel Moyer.

Data Collection

  • Converting DICOM format into PNG format: https://github.com/yehyunsuh/DICOM
  • Annotating landmarks: https://github.com/yehyunsuh/Landmark-Annotator

Environment

  • Ubuntu 22.04
  • CUDA 11.7
  • PyTorch 1.13.0

Training

  • Environment Setup conda create -n label_aug python=3.10 -y conda activate label_aug If you do not have conda downloaded in your setup, please refer to conda installation page.
  • Clone this repository and set up directories git clone https://github.com/vine-lab-vu/Label-Augmentation.git cd Label-Augmentation mkdir data && cd data mkdir -p image/all txt && cd ..
  • Put your data in the directories Label-Augmentation ├─ data │ ├─ image │ │ ├─ all │ │ │ ├─ 1.png │ │ │ ├─ 2.png │ │ │ ├─ ... │ │ │ └─ < here goes all the images > │ └─ txt │ ├─ test.txt │ └─ train.txt ├─ utility │ ├─ dataset.py │ ├─ log.py │ ├─ main.py │ ├─ model.py │ ├─ preprocess.py │ ├─ train.py │ └─ visualization.py ├─ dataset.py ├─ main.py ├─ test.py └─ train.py train.txt and test.txt come from Landmark-Annotator
  • Download libraries pip3 install -r requirements.txt
  • Start training python3 main.py --dilate number_of_dilation --dilation_decrease number_of_decrease_in_dilation --dilation_epoch how_many_epochs_per_each_dilation --image_resize size_of_resized_image --batch_size size_of_each_batch --output_channel number_of_labels If it is your first time training or have added new data, add --preprocess at the end of the command

Test

python3 main.py --test --output_channel number_of_labels If you have changed any other arguments that is related to the model, you have to add it to the test command.

Results

Landmark Prediction

Acknowledgement

This repository is built using the segmentation-models-pytorch library.

Citation

Yehyun Suh, Peter Chan, J. Ryan Martin, and Daniel Moyer. Label augmentation method for medical landmark detection in hip radiograph images, 2023. @misc{ suh2023label, title={Label Augmentation Method for Medical Landmark Detection in Hip Radiograph Images}, author={Yehyun Suh and Peter Chan and J. Ryan Martin and Daniel Moyer}, year={2023}, eprint={2309.16066}, archivePrefix={arXiv}, primaryClass={cs.LG} }

Owner

  • Name: vine-lab-vu
  • Login: vine-lab-vu
  • Kind: organization

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use label augmentation, please cite it as below."
authors:
- family-names: "Suh"
  given-names: "Yehyun"
title: "Label Augmentation Method for Medical Landmark Detection in Hip Radiograph Images"
version: 1.0.0
date-released: 2023-09-27
url: "https://github.com/vine-lab-vu/Label-Augmentation"
preferred-citation:
  type: generic
  authors:
  - family-names: "Suh"
    given-names: "Yehyun"
  - family-names: "Chan"
    given-names: "Peter"
  - family-names: "Martin"
    given-names: "J. Ryan"
  - family-names: "Moyer"
    given-names: "Daniel"
  doi: "doi.org/10.48550/arXiv.2309.16066"
  title: "Label Augmentation Method for Medical Landmark Detection in Hip Radiograph Images"
  month: 9
  year: 2023

GitHub Events

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Last Year
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Issues and Pull Requests

Last synced: 6 months ago

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  • Average comments per issue: 0.43
  • Average comments per pull request: 0
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  • Bot issues: 0
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Past Year
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  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
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  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
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Top Authors
Issue Authors
  • yehyunsuh (7)
Pull Request Authors
Top Labels
Issue Labels
enhancement (4) visualization (2) bug (1)
Pull Request Labels

Dependencies

requirements.txt pypi
  • albumentations ==1.3.1
  • pandas ==2.0.2
  • pydicom ==2.4.1
  • scipy ==1.11.0
  • segmentation-models-pytorch ==0.3.3
  • torch ==1.13.0
  • torchaudio ==0.13.0
  • torchvision ==0.14.0
  • tqdm ==4.65.0
  • wandb ==0.15.4