Cellular pattern recognition towards discrimination of normal skin from melanoma in non-invasive confocal imaging

Amy Swerdlin; Eric Simpson; Steven Jacques; Daniel S. Gareau

doi:10.1117/12.909892

22 February 2012 Cellular pattern recognition towards discrimination of normal skin from melanoma in non-invasive confocal imaging

Amy Swerdlin, Eric Simpson, Steven Jacques, Daniel S. Gareau

Author Affiliations +

Proceedings Volume 8214, Advanced Biomedical and Clinical Diagnostic Systems X; 82140C (2012) https://doi.org/10.1117/12.909892
Event: SPIE BiOS, 2012, San Francisco, California, United States

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.

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Amy Swerdlin, Eric Simpson, Steven Jacques, and Daniel S. Gareau "Cellular pattern recognition towards discrimination of normal skin from melanoma in non-invasive confocal imaging", Proc. SPIE 8214, Advanced Biomedical and Clinical Diagnostic Systems X, 82140C (22 February 2012); https://doi.org/10.1117/12.909892

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