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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