Lesion Analysis and Diagnosis with Mask-RCNN

10 Jul 2018 Andrey Sorokin

This project applies Mask R-CNN method to ISIC 2018 challenge tasks: lesion boundary segmentation (task1), lesion attributes detection (task 2), lesion diagnosis (task 3), a solution to the latter is using a trained model for task 1 and a simple voting procedure...

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Methods used in the Paper


METHOD TYPE
Softmax
Output Functions
Convolution
Convolutions
RoIAlign
RoI Feature Extractors
Mask R-CNN
Instance Segmentation Models