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End-User Skin Analysis (Moles) through Image Acquisition and Processing System

Skin moles and lesions can be the first signs of severe skin diseases such as cancer. This paper presents the development of an end-user device capable of capturing images, segmentation and diagnosis of moles by using the ABCD rule, which stands for analyzing moles’ parameters as: asymmetry, border,...

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Autores principales: Szolga, Lorant Andras, Bozga, Denisa Alice, Florea, Camelia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8839405/
https://www.ncbi.nlm.nih.gov/pubmed/35161868
http://dx.doi.org/10.3390/s22031123
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author Szolga, Lorant Andras
Bozga, Denisa Alice
Florea, Camelia
author_facet Szolga, Lorant Andras
Bozga, Denisa Alice
Florea, Camelia
author_sort Szolga, Lorant Andras
collection PubMed
description Skin moles and lesions can be the first signs of severe skin diseases such as cancer. This paper presents the development of an end-user device capable of capturing images, segmentation and diagnosis of moles by using the ABCD rule, which stands for analyzing moles’ parameters as: asymmetry, border, color, and diameter. These are the main mole characteristics that doctors look at, each of them having a different factor of importance, and depending on these an accurate diagnosis can be given. For the hardware, we developed a small and compact device that can be manipulated easily by anyone without knowledge of medicine, in which we considered a custom-designed 3D enclosure with two white LEDs to control the light. The device has the role of facilitating analysis of the suspicious moles regularly at home, even if only from an indicative and not from a medical point of view. The developed PC software permits the storage of the images in a local database for easy tracking and analysis in time. The image processing developed for the ABCD rule is incorporated into the PC software and tested extensively on the international PH2 database with skin melanoma images to validate our segmentation and criteria evaluation. Using the developed device, we captured mole images for patients, who also took a medical examination by a specialist using the standard dermatoscope. Therefore, we obtained our own database containing 26 images for which we have also the specialists’ diagnosis. The performance evaluation measures obtained using our device are—Accuracy: 0.92, Precision: 1.0, Recall: 0.92, F1-score: 0.96.
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spelling pubmed-88394052022-02-13 End-User Skin Analysis (Moles) through Image Acquisition and Processing System Szolga, Lorant Andras Bozga, Denisa Alice Florea, Camelia Sensors (Basel) Article Skin moles and lesions can be the first signs of severe skin diseases such as cancer. This paper presents the development of an end-user device capable of capturing images, segmentation and diagnosis of moles by using the ABCD rule, which stands for analyzing moles’ parameters as: asymmetry, border, color, and diameter. These are the main mole characteristics that doctors look at, each of them having a different factor of importance, and depending on these an accurate diagnosis can be given. For the hardware, we developed a small and compact device that can be manipulated easily by anyone without knowledge of medicine, in which we considered a custom-designed 3D enclosure with two white LEDs to control the light. The device has the role of facilitating analysis of the suspicious moles regularly at home, even if only from an indicative and not from a medical point of view. The developed PC software permits the storage of the images in a local database for easy tracking and analysis in time. The image processing developed for the ABCD rule is incorporated into the PC software and tested extensively on the international PH2 database with skin melanoma images to validate our segmentation and criteria evaluation. Using the developed device, we captured mole images for patients, who also took a medical examination by a specialist using the standard dermatoscope. Therefore, we obtained our own database containing 26 images for which we have also the specialists’ diagnosis. The performance evaluation measures obtained using our device are—Accuracy: 0.92, Precision: 1.0, Recall: 0.92, F1-score: 0.96. MDPI 2022-02-01 /pmc/articles/PMC8839405/ /pubmed/35161868 http://dx.doi.org/10.3390/s22031123 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Szolga, Lorant Andras
Bozga, Denisa Alice
Florea, Camelia
End-User Skin Analysis (Moles) through Image Acquisition and Processing System
title End-User Skin Analysis (Moles) through Image Acquisition and Processing System
title_full End-User Skin Analysis (Moles) through Image Acquisition and Processing System
title_fullStr End-User Skin Analysis (Moles) through Image Acquisition and Processing System
title_full_unstemmed End-User Skin Analysis (Moles) through Image Acquisition and Processing System
title_short End-User Skin Analysis (Moles) through Image Acquisition and Processing System
title_sort end-user skin analysis (moles) through image acquisition and processing system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8839405/
https://www.ncbi.nlm.nih.gov/pubmed/35161868
http://dx.doi.org/10.3390/s22031123
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