Cargando…
Computer-Aided Decision Support for Melanoma Detection Applied on Melanocytic and Nonmelanocytic Skin Lesions: A Comparison of Two Systems Based on Automatic Analysis of Dermoscopic Images
Commercially available clinical decision support systems (CDSSs) for skin cancer have been designed for the detection of melanoma only. Correct use of the systems requires expert knowledge, hampering their utility for nonexperts. Furthermore, there are no systems to detect other common skin cancer t...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4674594/ https://www.ncbi.nlm.nih.gov/pubmed/26693486 http://dx.doi.org/10.1155/2015/579282 |
_version_ | 1782404920829280256 |
---|---|
author | Møllersen, Kajsa Kirchesch, Herbert Zortea, Maciel Schopf, Thomas R. Hindberg, Kristian Godtliebsen, Fred |
author_facet | Møllersen, Kajsa Kirchesch, Herbert Zortea, Maciel Schopf, Thomas R. Hindberg, Kristian Godtliebsen, Fred |
author_sort | Møllersen, Kajsa |
collection | PubMed |
description | Commercially available clinical decision support systems (CDSSs) for skin cancer have been designed for the detection of melanoma only. Correct use of the systems requires expert knowledge, hampering their utility for nonexperts. Furthermore, there are no systems to detect other common skin cancer types, that is, nonmelanoma skin cancer (NMSC). As early diagnosis of skin cancer is essential, there is a need for a CDSS that is applicable to all types of skin lesions and is suitable for nonexperts. Nevus Doctor (ND) is a CDSS being developed by the authors. We here investigate ND's ability to detect both melanoma and NMSC and the opportunities for improvement. An independent test set of dermoscopic images of 870 skin lesions, including 44 melanomas and 101 NMSCs, were analysed by ND. Its sensitivity to melanoma and NMSC was compared to that of Mole Expert (ME), a commercially available CDSS, using the same set of lesions. ND and ME had similar sensitivity to melanoma. For ND at 95% melanoma sensitivity, the NMSC sensitivity was 100%, and the specificity was 12%. The melanomas misclassified by ND at 95% sensitivity were correctly classified by ME, and vice versa. ND is able to detect NMSC without sacrificing melanoma sensitivity. |
format | Online Article Text |
id | pubmed-4674594 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-46745942015-12-21 Computer-Aided Decision Support for Melanoma Detection Applied on Melanocytic and Nonmelanocytic Skin Lesions: A Comparison of Two Systems Based on Automatic Analysis of Dermoscopic Images Møllersen, Kajsa Kirchesch, Herbert Zortea, Maciel Schopf, Thomas R. Hindberg, Kristian Godtliebsen, Fred Biomed Res Int Research Article Commercially available clinical decision support systems (CDSSs) for skin cancer have been designed for the detection of melanoma only. Correct use of the systems requires expert knowledge, hampering their utility for nonexperts. Furthermore, there are no systems to detect other common skin cancer types, that is, nonmelanoma skin cancer (NMSC). As early diagnosis of skin cancer is essential, there is a need for a CDSS that is applicable to all types of skin lesions and is suitable for nonexperts. Nevus Doctor (ND) is a CDSS being developed by the authors. We here investigate ND's ability to detect both melanoma and NMSC and the opportunities for improvement. An independent test set of dermoscopic images of 870 skin lesions, including 44 melanomas and 101 NMSCs, were analysed by ND. Its sensitivity to melanoma and NMSC was compared to that of Mole Expert (ME), a commercially available CDSS, using the same set of lesions. ND and ME had similar sensitivity to melanoma. For ND at 95% melanoma sensitivity, the NMSC sensitivity was 100%, and the specificity was 12%. The melanomas misclassified by ND at 95% sensitivity were correctly classified by ME, and vice versa. ND is able to detect NMSC without sacrificing melanoma sensitivity. Hindawi Publishing Corporation 2015 2015-11-26 /pmc/articles/PMC4674594/ /pubmed/26693486 http://dx.doi.org/10.1155/2015/579282 Text en Copyright © 2015 Kajsa Møllersen et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Møllersen, Kajsa Kirchesch, Herbert Zortea, Maciel Schopf, Thomas R. Hindberg, Kristian Godtliebsen, Fred Computer-Aided Decision Support for Melanoma Detection Applied on Melanocytic and Nonmelanocytic Skin Lesions: A Comparison of Two Systems Based on Automatic Analysis of Dermoscopic Images |
title | Computer-Aided Decision Support for Melanoma Detection Applied on Melanocytic and Nonmelanocytic Skin Lesions: A Comparison of Two Systems Based on Automatic Analysis of Dermoscopic Images |
title_full | Computer-Aided Decision Support for Melanoma Detection Applied on Melanocytic and Nonmelanocytic Skin Lesions: A Comparison of Two Systems Based on Automatic Analysis of Dermoscopic Images |
title_fullStr | Computer-Aided Decision Support for Melanoma Detection Applied on Melanocytic and Nonmelanocytic Skin Lesions: A Comparison of Two Systems Based on Automatic Analysis of Dermoscopic Images |
title_full_unstemmed | Computer-Aided Decision Support for Melanoma Detection Applied on Melanocytic and Nonmelanocytic Skin Lesions: A Comparison of Two Systems Based on Automatic Analysis of Dermoscopic Images |
title_short | Computer-Aided Decision Support for Melanoma Detection Applied on Melanocytic and Nonmelanocytic Skin Lesions: A Comparison of Two Systems Based on Automatic Analysis of Dermoscopic Images |
title_sort | computer-aided decision support for melanoma detection applied on melanocytic and nonmelanocytic skin lesions: a comparison of two systems based on automatic analysis of dermoscopic images |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4674594/ https://www.ncbi.nlm.nih.gov/pubmed/26693486 http://dx.doi.org/10.1155/2015/579282 |
work_keys_str_mv | AT møllersenkajsa computeraideddecisionsupportformelanomadetectionappliedonmelanocyticandnonmelanocyticskinlesionsacomparisonoftwosystemsbasedonautomaticanalysisofdermoscopicimages AT kircheschherbert computeraideddecisionsupportformelanomadetectionappliedonmelanocyticandnonmelanocyticskinlesionsacomparisonoftwosystemsbasedonautomaticanalysisofdermoscopicimages AT zorteamaciel computeraideddecisionsupportformelanomadetectionappliedonmelanocyticandnonmelanocyticskinlesionsacomparisonoftwosystemsbasedonautomaticanalysisofdermoscopicimages AT schopfthomasr computeraideddecisionsupportformelanomadetectionappliedonmelanocyticandnonmelanocyticskinlesionsacomparisonoftwosystemsbasedonautomaticanalysisofdermoscopicimages AT hindbergkristian computeraideddecisionsupportformelanomadetectionappliedonmelanocyticandnonmelanocyticskinlesionsacomparisonoftwosystemsbasedonautomaticanalysisofdermoscopicimages AT godtliebsenfred computeraideddecisionsupportformelanomadetectionappliedonmelanocyticandnonmelanocyticskinlesionsacomparisonoftwosystemsbasedonautomaticanalysisofdermoscopicimages |