Lesion Analysis and Diagnosis with Mask-RCNN

Abstract

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.

4 pages, 4 figures, ISIC 2018 challenge

Cited by in corpus (1)

• Segmentation of Skin Lesions and their Attributes Using Multi-Scale Convolutional Neural Networks and Domain Specific Augmentations