Detection of the DEJ and segmentation of its morphological patterns in RCM images of melanocytic skin lesions Conference Paper


Authors: Kose, K.; Bozkurt, A.; Fox, C. A.; Gill, M.; Brooks, D.; Dy, J.; Rajadhyaksha, M.
Title: Detection of the DEJ and segmentation of its morphological patterns in RCM images of melanocytic skin lesions
Conference Title: Biomedical Optics 2020
Abstract: Reflectance confocal microscopy (RCM) provides a real-time noninvasive (in-vivo) proxy for histology. Here, we present machine learning models to delineate skin layers in RCM image stacks and analyze morphological patterns in RCM mosaics of skin. © 2020 The Author(s)
Keywords: in-vivo; reflectance confocal microscopies; image segmentation; real time; image stacks; melanocytic skin lesions; morphological patterns; machine learning models; skin layer
Journal Title OSA Technical Digest
Conference Dates: 2020 Apr 20-23
Conference Location: Virtual
ISBN: 978-1-943580-74-3
Publisher: Osa The Optical Society  
Date Published: 2020-01-01
Start Page: MW2A.1
Language: English
DOI: 10.1364/microscopy.2020.Mw2a.1
PROVIDER: scopus
DOI/URL:
Notes: Conference Paper -- Conference originally scheduled to take place in Washington DC, but moved to virtual format due to Covid 19 pandemic -- Export Date: 1 October 2020 -- Source: Scopus
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  1. Kivanc Kose
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