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code for paper Attention-based CNN for KL Grade Classification: Data from the Osteoarthritis Initiative

License: GNU Affero General Public License v3.0

Python 100.00%

oai-kl-grade-classification's Introduction

About

This Repo contains code for paper Attention-based CNN for KL Grade Classification: Data from the Osteoarthritis Initiative

Repo structure

  • ./data contains data for training/testing data for detector and classifier. OAI_summary.csv file is from OAI dataset, and contains metadata for all patients. The train/test split gave the performance mentioned in paper.
  • ./model_weights contains model weights that can be readily used by torch.load with the performance mentioned in paper.
  • ./oai-knee-detection contains code to train a detector and generate all annotations
  • ./oai-xray-klg contains code to train classifier and generate the attention map from GradCAM

Instruction

Please refer to requirements.txt for install all dependencies for this project. ./data folder contains example content file for train/test data used in dataloader for both detector and classifier. ./model_weights folder contains model weights that achieved the performance metrics mentioned in paper.

This repo consists of two parts. To reproduce the entire experiments, you will need to

  1. Train a detector and use the detector to annotate all OAI dataset, and generate train/test data for the classifier. See documentation in ./oai-knee-detection.
  2. Train and test the classifier by following documentation in ./oai-xray-klg

How to cite

@inproceedings{zhang2020attention,
  title={Attention-based cnn for kl grade classification: Data from the osteoarthritis initiative},
  author={Zhang, Bofei and Tan, Jimin and Cho, Kyunghyun and Chang, Gregory and Deniz, Cem M},
  booktitle={2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)},
  pages={731--735},
  year={2020},
  organization={IEEE}
}

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