Towards Skin Lesion Classification Using Machine Learning Algorithms and Stokes Imaging Polarimetry

Melanoma, the deadliest skin cancer, demands enhanced detection methods. A handheld device integrating polarimetric imaging and machine learning for lesion classification via the ABCDE method is proposed. Preliminary results indicate potential for improved diagnostic capabilities. © 2024 IEEE

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Publication Details

Published
2024-08-04
DOI
https://doi.org/10.1109/cleo-pr60912.2024.10676598
Primary Topic
Optical Polarization and Ellipsometry
Type
article
Field-Weighted Citation Impact
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article

Towards Skin Lesion Classification Using Machine Learning Algorithms and Stokes Imaging Polarimetry

Geminiano Martínez‐Ponce, Oscar I. Rodríguez-Cortés
Optical Polarization and Ellipsometry
article

Towards Skin Lesion Classification Using Machine Learning Algorithms and Stokes Imaging Polarimetry

Geminiano Martínez‐Ponce, Oscar I. Rodríguez-Cortés
article en

Abstract

Melanoma, the deadliest skin cancer, demands enhanced detection methods. A handheld device integrating polarimetric imaging and machine learning for lesion classification via the ABCDE method is proposed. Preliminary results indicate potential for improved diagnostic capabilities. © 2024 IEEE

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Optical Polarization and Ellipsometry
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Towards Skin Lesion Classification Using Machine Learning Algorithms and Stokes Imaging Polarimetry — Geminiano Martínez‐Ponce, Oscar I. Rodríguez-Cortés · (2024) | TGRS Research Map | TGRS