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Conference Paper/Proceeding/Abstract 1543 views 258 downloads

Melanoma detection using a mobile phone app

Luciano E. Diniz, K. Ennser, Karin Ennser

SPEI Photonic West: Optics and Biophotonics in Low-Resource Settings II, Volume: 9699, Start page: 96990V

Swansea University Author: Karin Ennser

DOI (Published version): 10.1117/12.2212446

Abstract

Mobile phones have had their processing power greatly increased since their invention. As a direct result of Moore’s Law, this improvement has made available several applications that were impossible before due to the portability and popularity. The aim of this paper is to develop a mobile phone app...

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Published in: SPEI Photonic West: Optics and Biophotonics in Low-Resource Settings II
Published: 2016
URI: https://cronfa.swan.ac.uk/Record/cronfa28891
first_indexed 2016-06-15T19:04:19Z
last_indexed 2018-02-09T05:13:28Z
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spelling 2016-10-04T14:32:21.4271297 v2 28891 2016-06-15 Melanoma detection using a mobile phone app 0aa21e9e51bfb74793881e5780d29ae8 Karin Ennser Karin Ennser true false 2016-06-15 ACEM Mobile phones have had their processing power greatly increased since their invention. As a direct result of Moore’s Law, this improvement has made available several applications that were impossible before due to the portability and popularity. The aim of this paper is to develop a mobile phone app, integrated with its camera coupled to an amplifying lens, to help distinguish melanoma. The proposed application has the capability of processing skin mole images and suggesting, using a score system, if it is a case of melanoma or not. This score system is based on the ABCDE signs of melanoma, and takes into account the area, the perimeter and the colors present in the nevus of a human skin. The app has been calibrated and tested using images from the PH2 Dermoscopic Image Database from Pedro Hispano Hospital. The results show that the mobile app created can be useful, with an accuracy of up to 100% for malign cases and 80% for benign cases (including common and atypical moles), when used in the test group with less than a minute procesing time. Conference Paper/Proceeding/Abstract SPEI Photonic West: Optics and Biophotonics in Low-Resource Settings II 9699 96990V melanoma, skin cancer, android tecnology, application, database, e-heatlh 7 3 2016 2016-03-07 10.1117/12.2212446 COLLEGE NANME Aerospace, Civil, Electrical, and Mechanical Engineering COLLEGE CODE ACEM Swansea University Brazilian Science without Border Programme 2016-10-04T14:32:21.4271297 2016-06-15T13:53:17.6627010 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering Luciano E. Diniz 1 K. Ennser 2 Karin Ennser 3 0028891-15062016155658.pdf SPIE-Melanomadetection17feb2016.pdf 2016-06-15T15:56:58.0830000 Output 14998137 application/pdf Accepted Manuscript true 2016-06-15T00:00:00.0000000 true
title Melanoma detection using a mobile phone app
spellingShingle Melanoma detection using a mobile phone app
Karin Ennser
title_short Melanoma detection using a mobile phone app
title_full Melanoma detection using a mobile phone app
title_fullStr Melanoma detection using a mobile phone app
title_full_unstemmed Melanoma detection using a mobile phone app
title_sort Melanoma detection using a mobile phone app
author_id_str_mv 0aa21e9e51bfb74793881e5780d29ae8
author_id_fullname_str_mv 0aa21e9e51bfb74793881e5780d29ae8_***_Karin Ennser
author Karin Ennser
author2 Luciano E. Diniz
K. Ennser
Karin Ennser
format Conference Paper/Proceeding/Abstract
container_title SPEI Photonic West: Optics and Biophotonics in Low-Resource Settings II
container_volume 9699
container_start_page 96990V
publishDate 2016
institution Swansea University
doi_str_mv 10.1117/12.2212446
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering
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description Mobile phones have had their processing power greatly increased since their invention. As a direct result of Moore’s Law, this improvement has made available several applications that were impossible before due to the portability and popularity. The aim of this paper is to develop a mobile phone app, integrated with its camera coupled to an amplifying lens, to help distinguish melanoma. The proposed application has the capability of processing skin mole images and suggesting, using a score system, if it is a case of melanoma or not. This score system is based on the ABCDE signs of melanoma, and takes into account the area, the perimeter and the colors present in the nevus of a human skin. The app has been calibrated and tested using images from the PH2 Dermoscopic Image Database from Pedro Hispano Hospital. The results show that the mobile app created can be useful, with an accuracy of up to 100% for malign cases and 80% for benign cases (including common and atypical moles), when used in the test group with less than a minute procesing time.
published_date 2016-03-07T06:58:23Z
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score 11.3254

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