Cargando…
Abrupt skin lesion border cutoff measurement for malignancy detection in dermoscopy images
BACKGROUND: Automated skin lesion border examination and analysis techniques have become an important field of research for distinguishing malignant pigmented lesions from benign lesions. An abrupt pigment pattern cutoff at the periphery of a skin lesion is one of the most important dermoscopic feat...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5073935/ https://www.ncbi.nlm.nih.gov/pubmed/27766942 http://dx.doi.org/10.1186/s12859-016-1221-4 |
_version_ | 1782461661669490688 |
---|---|
author | Kaya, Sertan Bayraktar, Mustafa Kockara, Sinan Mete, Mutlu Halic, Tansel Field, Halle E. Wong, Henry K. |
author_facet | Kaya, Sertan Bayraktar, Mustafa Kockara, Sinan Mete, Mutlu Halic, Tansel Field, Halle E. Wong, Henry K. |
author_sort | Kaya, Sertan |
collection | PubMed |
description | BACKGROUND: Automated skin lesion border examination and analysis techniques have become an important field of research for distinguishing malignant pigmented lesions from benign lesions. An abrupt pigment pattern cutoff at the periphery of a skin lesion is one of the most important dermoscopic features for detection of neoplastic behavior. In current clinical setting, the lesion is divided into a virtual pie with eight sections. Each section is examined by a dermatologist for abrupt cutoff and scored accordingly, which can be tedious and subjective. METHODS: This study introduces a novel approach to objectively quantify abruptness of pigment patterns along the lesion periphery. In the proposed approach, first, the skin lesion border is detected by the density based lesion border detection method. Second, the detected border is gradually scaled through vector operations. Then, along gradually scaled borders, pigment pattern homogeneities are calculated at different scales. Through this process, statistical texture features are extracted. Moreover, different color spaces are examined for the efficacy of texture analysis. RESULTS: The proposed method has been tested and validated on 100 (31 melanoma, 69 benign) dermoscopy images. Analyzed results indicate that proposed method is efficient on malignancy detection. More specifically, we obtained specificity of 0.96 and sensitivity of 0.86 for malignancy detection in a certain color space. The F-measure, harmonic mean of recall and precision, of the framework is reported as 0.87. CONCLUSIONS: The use of texture homogeneity along the periphery of the lesion border is an effective method to detect malignancy of the skin lesion in dermoscopy images. Among different color spaces tested, RGB color space’s blue color channel is the most informative color channel to detect malignancy for skin lesions. That is followed by YCbCr color spaces Cr channel, and Cr is closely followed by the green color channel of RGB color space. |
format | Online Article Text |
id | pubmed-5073935 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-50739352016-10-26 Abrupt skin lesion border cutoff measurement for malignancy detection in dermoscopy images Kaya, Sertan Bayraktar, Mustafa Kockara, Sinan Mete, Mutlu Halic, Tansel Field, Halle E. Wong, Henry K. BMC Bioinformatics Proceedings BACKGROUND: Automated skin lesion border examination and analysis techniques have become an important field of research for distinguishing malignant pigmented lesions from benign lesions. An abrupt pigment pattern cutoff at the periphery of a skin lesion is one of the most important dermoscopic features for detection of neoplastic behavior. In current clinical setting, the lesion is divided into a virtual pie with eight sections. Each section is examined by a dermatologist for abrupt cutoff and scored accordingly, which can be tedious and subjective. METHODS: This study introduces a novel approach to objectively quantify abruptness of pigment patterns along the lesion periphery. In the proposed approach, first, the skin lesion border is detected by the density based lesion border detection method. Second, the detected border is gradually scaled through vector operations. Then, along gradually scaled borders, pigment pattern homogeneities are calculated at different scales. Through this process, statistical texture features are extracted. Moreover, different color spaces are examined for the efficacy of texture analysis. RESULTS: The proposed method has been tested and validated on 100 (31 melanoma, 69 benign) dermoscopy images. Analyzed results indicate that proposed method is efficient on malignancy detection. More specifically, we obtained specificity of 0.96 and sensitivity of 0.86 for malignancy detection in a certain color space. The F-measure, harmonic mean of recall and precision, of the framework is reported as 0.87. CONCLUSIONS: The use of texture homogeneity along the periphery of the lesion border is an effective method to detect malignancy of the skin lesion in dermoscopy images. Among different color spaces tested, RGB color space’s blue color channel is the most informative color channel to detect malignancy for skin lesions. That is followed by YCbCr color spaces Cr channel, and Cr is closely followed by the green color channel of RGB color space. BioMed Central 2016-10-06 /pmc/articles/PMC5073935/ /pubmed/27766942 http://dx.doi.org/10.1186/s12859-016-1221-4 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Proceedings Kaya, Sertan Bayraktar, Mustafa Kockara, Sinan Mete, Mutlu Halic, Tansel Field, Halle E. Wong, Henry K. Abrupt skin lesion border cutoff measurement for malignancy detection in dermoscopy images |
title | Abrupt skin lesion border cutoff measurement for malignancy detection in dermoscopy images |
title_full | Abrupt skin lesion border cutoff measurement for malignancy detection in dermoscopy images |
title_fullStr | Abrupt skin lesion border cutoff measurement for malignancy detection in dermoscopy images |
title_full_unstemmed | Abrupt skin lesion border cutoff measurement for malignancy detection in dermoscopy images |
title_short | Abrupt skin lesion border cutoff measurement for malignancy detection in dermoscopy images |
title_sort | abrupt skin lesion border cutoff measurement for malignancy detection in dermoscopy images |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5073935/ https://www.ncbi.nlm.nih.gov/pubmed/27766942 http://dx.doi.org/10.1186/s12859-016-1221-4 |
work_keys_str_mv | AT kayasertan abruptskinlesionbordercutoffmeasurementformalignancydetectionindermoscopyimages AT bayraktarmustafa abruptskinlesionbordercutoffmeasurementformalignancydetectionindermoscopyimages AT kockarasinan abruptskinlesionbordercutoffmeasurementformalignancydetectionindermoscopyimages AT metemutlu abruptskinlesionbordercutoffmeasurementformalignancydetectionindermoscopyimages AT halictansel abruptskinlesionbordercutoffmeasurementformalignancydetectionindermoscopyimages AT fieldhallee abruptskinlesionbordercutoffmeasurementformalignancydetectionindermoscopyimages AT wonghenryk abruptskinlesionbordercutoffmeasurementformalignancydetectionindermoscopyimages |