Paper
20 December 2021 Polarization-based skin cancer detection in vivo
Author Affiliations +
Proceedings Volume 12126, Fifteenth International Conference on Correlation Optics; 121262P (2021) https://doi.org/10.1117/12.2621081
Event: Fifteenth International Conference on Correlation Optics, 2021, Chernivtsi, Ukraine
Abstract
Recently optical imaging is focused on non-invasive methods which could be automated and provide diagnostics in vivo. Coherence and polarization encoding the wave phase transformation create additional channels of information compared with the amplitude-based techniques. The modification of polarization properties like depolarization, birefringence, and diattenuation are the subject of polarimetry. One of the depolarization metrics is the Degree of Polarization (DOP), which represent the fraction of polarized light maintained while light propagates in media, ranging from 1 for fully polarized to 0 for totally depolarized light. After constructing a one-shot Stokes polarimetry probe, we conducted a preliminary clinical trial including 20 benign, 28 malignant skin lesions. Also 59 normal skin sites where tested. Using DOP as a diagnostics criterion we were able to separate Malignant Melanomas against all other lesions. Another depolarization metric tested was the Polarization Memory Rate (PMR) which characterizes the decay of circularly polarized light relative to linearly polarized light as light propagates in a medium. PMR demonstrates a strong diagnostics potential separating all cancer against benign lesions.
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lioudmila Tchvialeva, Daniel C. Louie, Yuheng Wang, Sunil Kalia, Harvey Lui, and Tim K. Lee "Polarization-based skin cancer detection in vivo", Proc. SPIE 12126, Fifteenth International Conference on Correlation Optics, 121262P (20 December 2021); https://doi.org/10.1117/12.2621081
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KEYWORDS
Polarization

Skin

Cancer

Skin cancer

Polarimetry

Diagnostics

In vivo imaging

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