Study of skin cancer lesions through multispectral and 3D techniques

Laura Rey-Barroso; Francisco J. Burgos-Fernández; Miguel Ares; Santiago Royo; Xana Delpueyo; Susana Puig; Josep Malvehy; Giovanni Pellacani; Meritxell Vilaseca

doi:10.1117/12.2526970

19 July 2019 Study of skin cancer lesions through multispectral and 3D techniques

Laura Rey-Barroso, Francisco J. Burgos-Fernández, Miguel Ares, Santiago Royo, Xana Delpueyo, Susana Puig, Josep Malvehy, Giovanni Pellacani, Meritxell Vilaseca

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Proceedings Volume 11073, Clinical and Preclinical Optical Diagnostics II; 110730B (2019) https://doi.org/10.1117/12.2526970
Event: European Conferences on Biomedical Optics, 2019, Munich, Germany

Abstract

The effective and non-invasive diagnosis of skin cancer is a hot topic in biophotonics since the current gold standard, biopsy followed by histological examination, is a slow and costly procedure for the healthcare system. Therefore, authors have put their efforts in characterizing skin cancer quantitatively through optical and photonic techniques such as 3D topography and multispectral imaging. Skin relief is an important biophysical feature that can be difficult to appreciate by touch, but can be precisely characterized with 3D imaging techniques, such as fringe projection. Color and spectral features given by skin chromophores, which are routinely analyzed by the naked eye and through dermoscopy, can also be quantified by means of multispectral imaging systems. In this study, the outcomes of these two imaging modalities were combined in a machine learning process to enhance classification of melanomas and nevi obtained from the two systems when operating isolately. The results suggest that the combination of 3D and multispectral data is relevant for the medical diagnosis of skin cancer.

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Laura Rey-Barroso, Francisco J. Burgos-Fernández, Miguel Ares, Santiago Royo, Xana Delpueyo, Susana Puig, Josep Malvehy, Giovanni Pellacani, and Meritxell Vilaseca "Study of skin cancer lesions through multispectral and 3D techniques", Proc. SPIE 11073, Clinical and Preclinical Optical Diagnostics II, 110730B (19 July 2019); https://doi.org/10.1117/12.2526970

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KEYWORDS

Skin cancer

Skin

Melanoma

3D image processing

3D modeling

Statistical analysis

Imaging systems

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