MAX-Breast-Cancer-Mitosis-Detector - Detect whether a mitosis exists in an image of breast cancer tumor cells

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The Tumor Proliferation Assessment Challenge 2016 (TUPAC16) was created to develop state-of-the-art algorithms for automatic prediction of tumor proliferation scores from whole-slide histopathology images of breast tumors. The IBM CODAIT team trained a mitosis detection model (a modified ResNet-50 model) on the TUPAC16 auxiliary mitosis dataset, and then applied it to the whole slide images for predicting the tumor proliferation scores. This repository contains code to instantiate and deploy the mitosis detection model mentioned above. This model takes a 64 x 64 PNG image file extracted from the whole slide image as input, and outputs the predicted probability of the image containing mitosis. For more information and additional features, check out the deep-histopath repository on GitHub.

https://github.com/IBM/MAX-Breast-Cancer-Mitosis-Detector

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