Bone age assessment

This implementation is base on the paper on the Bone age assessment based on deep neural networks with annotation-free cascaded critical bone region extraction by Zhangyong Li et al. The paper is available here.

The implementation is done using the Pytorch framework. The model is trained on the RSNA Bone Age dataset. The dataset is available here.

The dataset is expected in the folder data/ in the root directory of the project. The dataset should be in the following format:

data/
    - boneage-test-dataset/
        - 1.png
        - 2.png
        - ...
    - boneage-train-dataset/
        - 1.png
        - 2.png
        - ...

Goal

This is the first approach to create the algorithm for the bone age assessment. In the long run, I want to apply this to dolphin pectoral fins to assess their age.