Novel Method for Border Irregularity Assessment in Dermoscopic Color Images

Background. One of the most important lesion features predicting malignancy is border irregularity. Accurate assessment of irregular borders is clinically important due to significantly different occurrence in benign and malignant skin lesions. Method. In this research, we present a new approach for...

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Main Author: Joanna Jaworek-Korjakowska
Format: Article
Language:English
Published: Hindawi Limited 2015-01-01
Series:Computational and Mathematical Methods in Medicine
Online Access:http://dx.doi.org/10.1155/2015/496202
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spelling doaj-8b09720768e541c0a6451c830c1bbaff2020-11-24T21:23:51ZengHindawi LimitedComputational and Mathematical Methods in Medicine1748-670X1748-67182015-01-01201510.1155/2015/496202496202Novel Method for Border Irregularity Assessment in Dermoscopic Color ImagesJoanna Jaworek-Korjakowska0Department of Automatics and Biomedical Engineering, AGH University of Science and Technology, Aleja Mickiewicza 30, 30-059 Krakow, PolandBackground. One of the most important lesion features predicting malignancy is border irregularity. Accurate assessment of irregular borders is clinically important due to significantly different occurrence in benign and malignant skin lesions. Method. In this research, we present a new approach for the detection of border irregularities, as one of the major parameters in a widely used diagnostic algorithm the ABCD rule of dermoscopy. The proposed work is focused on designing an efficient automatic algorithm containing the following steps: image enhancement, lesion segmentation, borderline calculation, and irregularities detection. The challenge lies in determining the exact borderline. For solving this problem we have implemented a new method based on lesion rotation and borderline division. Results. The algorithm has been tested on 350 dermoscopic images and achieved accuracy of 92% indicating that the proposed computational approach captured most of the irregularities and provides reliable information for effective skin mole examination. Compared to the state of the art, we obtained improved classification results. Conclusions. The current study suggests that computer-aided system is a practical tool for dermoscopic image assessment and could be recommended for both research and clinical applications. The proposed algorithm can be applied in different fields of medical image analysis including, for example, CT and MRI images.http://dx.doi.org/10.1155/2015/496202
collection DOAJ
language English
format Article
sources DOAJ
author Joanna Jaworek-Korjakowska
spellingShingle Joanna Jaworek-Korjakowska
Novel Method for Border Irregularity Assessment in Dermoscopic Color Images
Computational and Mathematical Methods in Medicine
author_facet Joanna Jaworek-Korjakowska
author_sort Joanna Jaworek-Korjakowska
title Novel Method for Border Irregularity Assessment in Dermoscopic Color Images
title_short Novel Method for Border Irregularity Assessment in Dermoscopic Color Images
title_full Novel Method for Border Irregularity Assessment in Dermoscopic Color Images
title_fullStr Novel Method for Border Irregularity Assessment in Dermoscopic Color Images
title_full_unstemmed Novel Method for Border Irregularity Assessment in Dermoscopic Color Images
title_sort novel method for border irregularity assessment in dermoscopic color images
publisher Hindawi Limited
series Computational and Mathematical Methods in Medicine
issn 1748-670X
1748-6718
publishDate 2015-01-01
description Background. One of the most important lesion features predicting malignancy is border irregularity. Accurate assessment of irregular borders is clinically important due to significantly different occurrence in benign and malignant skin lesions. Method. In this research, we present a new approach for the detection of border irregularities, as one of the major parameters in a widely used diagnostic algorithm the ABCD rule of dermoscopy. The proposed work is focused on designing an efficient automatic algorithm containing the following steps: image enhancement, lesion segmentation, borderline calculation, and irregularities detection. The challenge lies in determining the exact borderline. For solving this problem we have implemented a new method based on lesion rotation and borderline division. Results. The algorithm has been tested on 350 dermoscopic images and achieved accuracy of 92% indicating that the proposed computational approach captured most of the irregularities and provides reliable information for effective skin mole examination. Compared to the state of the art, we obtained improved classification results. Conclusions. The current study suggests that computer-aided system is a practical tool for dermoscopic image assessment and could be recommended for both research and clinical applications. The proposed algorithm can be applied in different fields of medical image analysis including, for example, CT and MRI images.
url http://dx.doi.org/10.1155/2015/496202
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