Dermoscopy image analysis in the age of deep learning

M. Emre Celebi

doi:10.1117/12.2588612

5 March 2021 Dermoscopy image analysis in the age of deep learning

M. Emre Celebi

Proceedings Volume 11618, Photonics in Dermatology and Plastic Surgery 2021; 1161813 (2021) https://doi.org/10.1117/12.2588612
Event: SPIE BiOS, 2021, Online Only

Abstract

Dermoscopy is a non-invasive skin imaging technique that permits visualization of features of pigmented melanocytic neoplasms that are not discernable by examination with the naked eye. While studies on the automated analysis of dermoscopy images date back to the mid-1990s, because of various factors (lack of publicly available datasets, open-source software, computational power, etc.), the field progressed rather slowly in its first two decades. With the release of a large public dataset by the International Skin Imaging Collaboration in 2016, development of open-source software for convolutional neural networks, and the availability of inexpensive graphics processing units, dermoscopy image analysis has recently become a very active research field. In this talk, I will first present a historical overview of dermoscopy image analysis and then discuss the latest developments in this field that were prompted by the deep learning revolution.

Conference Presentation

Citation Download Citation

M. Emre Celebi "Dermoscopy image analysis in the age of deep learning", Proc. SPIE 11618, Photonics in Dermatology and Plastic Surgery 2021, 1161813 (5 March 2021); https://doi.org/10.1117/12.2588612

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