Abstract
Melanoma is the most deadly form of skin cancer worldwide. Many efforts have been made for early detection of melanoma. The International Skin Imaging Collaboration (ISIC) hosted the 2018 Challenges to help the diagnosis of melanoma based on dermoscopic images. In this paper, we describe our solutions for the task 2 of ISIC 2018 Challenges. We present two deep learning approaches to automatically detect lesion attributes of melanoma, one is a U-Net based model and the other is a Mask R-CNN based model. The Jaccard index on official validation data is 0.477 and 0.233, respectively. The code for our solutions is publicly available.
Copyright
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