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Proceedings Paper

Cellular pattern recognition towards discrimination of normal skin from melanoma in non-invasive confocal imaging
Author(s): Amy Swerdlin; Eric Simpson; Steven Jacques; Daniel S. Gareau
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Paper Abstract

Cellular histopathological melanoma screening is critical but expensive/invasive. Confocal screening is cheap/noninvasive but data interpretation remains difficult. Human terminology for biological features is insufficient to fully exploit the diagnostic value, so we propose automated quantitative morphometry. Normal diagnostic traits include a regularly organized spinous keratinocyte matrix on an underlying smooth basal keritinocyte layer. Computational identification of dark nuclei in spinous keratinocytes and bright pigmented basal keratinocytes yields two distinct regions: basal and super-basal. These independent algorithms usually yield complementary regions but occasionally overlap or leave gaps. Improved microanatomical discrimination will yield a better diagnostic map to evaluate morphology for cancer detection.

Paper Details

Date Published: 22 February 2012
PDF: 4 pages
Proc. SPIE 8214, Advanced Biomedical and Clinical Diagnostic Systems X, 82140C (22 February 2012); doi: 10.1117/12.909892
Show Author Affiliations
Amy Swerdlin, Oregon Health & Science Univ. (United States)
Eric Simpson, Oregon Health & Science Univ. (United States)
Steven Jacques, Oregon Health & Science Univ. (United States)
Daniel S. Gareau, Oregon Health & Science Univ. (United States)
The Rockefeller Univ. (United States)

Published in SPIE Proceedings Vol. 8214:
Advanced Biomedical and Clinical Diagnostic Systems X
Tuan Vo-Dinh; Anita Mahadevan-Jansen; Warren S. Grundfest, Editor(s)

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