Oct 20 – 25, 2019
America/Mexico_City timezone

Skin Lesion Detection in Dermatological Images using Deep Learning

Oct 22, 2019, 5:40 PM
20m

Speaker

José Carlos Moreno-Tagle (UNAM)

Description

We demonstrate that it is possible to approach the skin lesion classification problem as a detection problem (multiple localization with classification), a much more complex and interesting problem with satisfactory and promising results. The image dataset used in the experiments comes from the ISIC Dermoscopic Archive, an open-access dermatology repository. In particular, the ISIC 2017 dataset, a subset of the ISIC archive, released for the annual ISIC challenge was used. We show that it is possible to adapt a high quality imaging dataset to the requirements demanded by a deep learning detection architecture such as YOLOv3 [10]. After the training process is completed, the detector is able to identify and locate three different types of skin lesions in real-time. Finally, we describe some of the next steps we are taking to improve the performance of this proposed solution as we seek to deploy in the near future a real-time deep learning solution in a smartphone app that could be used by a medical specialist as well as the general public.

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