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Matthews Correlation Coefficient Loss implementation for image segmentation.

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Matthews Correlation Coefficient Loss for Deep Convolutional Networks: Application to Skin Lesion Segmentation

Code style: black

Skin lesion segmentation masks overlap

This is the code corresponding to our ISBI 2021 paper. If you use our code, please cite our paper:

Kumar Abhishek, Ghassan Hamarneh, "Matthews Correlation Coefficient Loss for Deep Convolutional Networks: Application to Skin Lesion Segmentation", The IEEE International Symposium on Biomedical Imaging (ISBI), 2021.

The corresponding bibtex entry is:

@InProceedings{Abhishek_2021_ISBI,
author = {Abhishek, Kumar and Hamarneh, Ghassan},
title = {Matthews Correlation Coefficient Loss for Deep Convolutional Networks: Application to Skin Lesion Segmentation},
booktitle = {The IEEE International Symposium on Biomedical Imaging (ISBI)},
month = {April},
year = {2021}
}

Dependencies

  • PyTorch

Usage

An example usage is shown in Example.ipynb, where the Dice and MCC losses are calculated for a simple scenario of 5x5 ground truth and predicted binary masks.