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

MCC Loss is now available in smp Segmentation Models PyTorch as smp.losses.MCCLoss.

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)},,
pages={225--229},
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.