oseynnes/dl_track

A deep learning approach for analysing muscle architecture from musculoskeletal ultrasound images

DL_Track

A deep learning approach for analysing muscle architecture from musculoskeletal ultrasound images.

To start using this software on your own computer, first use the setup instructions.

To train your own model, you can add your own images and labels to those that are provided, or you can create your own dataset (labelling instructions can be found here). Then use the 'Model_Training.ipynb' notebook to train your model (NOTE: Use a GPU!).

To use my trained models to analyse your own data, simply run the 'Inference_Single_Image.ipynb' or 'Inference_Video.ipynb' Jupyter notebook to analyse individual images or videos respectively. Note that in your images/videos, the fascicles should be oriented from bottom-left to top-right (see image below). If they are not, set the 'flip' variable in the notebook to 1 instead of 0.

If you don't have access to a GPU or couldn't get the main version working, try using the colab version (instructions here). This is more limited, but most of the functionality is the same.

If you find this work useful, please cite the corresponding paper: Link coming soon