Source code accompanying ISBI 2022 publication, https://arxiv.org/abs/2201.10849:
-
The code requires the OAI Baseline/00m dataset - textual variables and SAG 3D DESS MR images.
-
Create a Conda environment from
environment.yml
. Install the code as a Python module. -
See
entry/runner.sh
for the complete workflow. -
The structure of the original project is as follows:
./project/ | data/ # preprocessed scans and variables | OAI_Clin_prep/ | meta_base.csv | OAI_SAG_3D_DESS_prep/ | OAI_XR_PA_prep/ | src/ (this repository) | results/ # model weights, intermediate and final results | experiment_0/ | weights/ | ... | experiment_1/ | ...
This code is freely available for research purposes.
The software has not been certified as a medical device and, therefore, must not be used for diagnostic purposes in a real clinical scenario.
@inproceedings{panfilov2022predicting,
title={Predicting Knee Osteoarthritis Progression from Structural {MRI} Using Deep Learning},
author={Panfilov, Egor and Saarakkala, Simo and Nieminen, Miika T and Tiulpin, Aleksei},
booktitle={2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)},
pages={1--5},
year={2022},
organization={IEEE}
}