Codes for paper Automatic Knee Osteoarthritis Diagnosis from Plain Radiographs: A Deep Learning-Based Approach.
Aleksei Tiulpin, Jérôme Thevenot, Esa Rahtu, Petri Lehenkari, and Simo Saarakkala, 2017.
Osteoarthritis (OA) is the 11th highest disability factor and it is associated with the cartilage and bone degeneration in the joints. The most common type of is knee OA and it is causing an extremly high economical burden to the society while being difficult to diagnose. In this study we present a novel Deep Learning-based approach to diagnose knee osteoarthritis from plain radiographs (X-ray images).
Here we present the training codes and the pretrained models from each of our experiments. Please, see the paper for more details.
To run the experiments, you should have the following main demendencies:
- pytorch
- PIL
- matplotlib
- Jupyter Notebook (to work with attention maps)
- tqdm
- visdom
- numpy
- termcolor
- torchvision
run corresponding bash files to obtain the results (validation is visualized in visdom).
This code is freely available only for research purpuses.