Identification of Melanoma Diseases from Multispectral Dermatological Images Using a Novel BSS Approach

Zokay, Mustapha; Saylani, Hicham

doi:10.1007/978-981-16-6775-6_13

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2024

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Cited by 2 publications

References 15 publications

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Identification of Skin Diseases Based on Blind Chromophore Separation and Artificial Intelligence

Zokay,

Saylani

2024

Lecture Notes in Computer Science

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Identification of Skin Diseases Based on Blind Chromophore Separation and Artificial Intelligence

Zokay,

Saylani

2024

Lecture Notes in Computer Science

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Blind Separation of Skin Chromophores from Multispectral Dermatological Images

Zokay,

Saylani

2024

Diagnostics

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Background/Objectives: Based on Blind Source Separation and the use of multispectral imaging, the new approach we propose in this paper aims to improve the estimation of the concentrations of the main skin chromophores (melanin, oxyhemoglobin and deoxyhemoglobin), while considering shading as a fully-fledged source. Methods: In this paper, we demonstrate that the use of the Infra-Red spectral band, in addition to the traditional RGB spectral bands of dermatological images, allows us to model the image provided by each spectral band as a mixture of the concentrations of the three chromophores in addition to that of the shading, which are estimated through four steps using Blind Source Separation. Results: We studied the performance of our new method on a database of real multispectral dermatological images of melanoma by proposing a new quantitative performances measurement criterion based on mutual information. We then validated these performances on a database of multispectral dermatological images that we simulated using our own new protocol. Conclusions: All the results obtained demonstrated the effectiveness of our new approach for estimating the concentrations of the skin chromophores from a multispectral dermatological image, compared to traditional approaches that consist of using only the RGB image by neglecting shading.

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Identification of Melanoma Diseases from Multispectral Dermatological Images Using a Novel BSS Approach

Cited by 2 publications

References 15 publications

Identification of Skin Diseases Based on Blind Chromophore Separation and Artificial Intelligence

Identification of Skin Diseases Based on Blind Chromophore Separation and Artificial Intelligence

Blind Separation of Skin Chromophores from Multispectral Dermatological Images

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