This repository was used to develop AsymMirai. The codebase itself is a fork of the MIT-licensed Mirai codebase (https://github.com/yala/Mirai). Because AsymMirai also relies on the Mirai backbone, most of the Mirai code is retained in this repository. See README_mirai.md for details on the parts of the codebase original to Mirai.
AsymMirai was primarily trained and evaluated on the EMory BrEast imaging Dataset (EMBED); as such, it assumes the information described in the EMBED documentation is available. This dataset is available upon request; instructions to gain access are available in the EMBED documentation.
This implementation assumes there exists a CSV file of the form shown in example_data_format.csv with the path to each image and metadata for a series of exams.
The jupyter notebook asymmetry_model/run_train.ipynb provides an example of the call to train AsymMirai. In order to train AsymMirai, you will need to download the publicly trained weights from Mirai's backbone and place them in a directory named snapshots in the root directory for this repository. These weights are available here.
The jupyter notebook asymmetry_model/run_eval.ipynb provides an example of the code used to evaluate a trained AsymMirai. This code runs AsymMirai over each exam in the indicated CSV file, and records the risk score and prediction window location for each sample.
The jupyter notebook additional_asymmirai_experiments.ipynb provides the code used to analyze AsymMirai, producing ROC curves.