Presentation
5 March 2021 Dermoscopy image analysis in the age of deep learning
Author Affiliations +
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
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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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KEYWORDS
Image analysis

Skin

Software development

Convolutional neural networks

Eye

Graphics processing units

Visualization

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