RESEARCH ARTICLE
Epiluminescence Image Processing for Melanocytic Skin Lesion Diagnosis Based on 7-Point Check-List: A Preliminary Discussion on Three Parameters
Gabriella Fabbrocini*, 1, Giovanni Betta2, Giuseppe Di Leo3, Consolatina Liguori3, Alfredo Paolillo3, Antonio Pietrosanto3, Paolo Sommella3, Orsola Rescigno1, Sara Cacciapuoti1, Francesco Pastore1, Valerio De Vita1, Ines Mordente1, Fabio Ayala1
Article Information
Identifiers and Pagination:
Year: 2010Volume: 4
First Page: 110
Last Page: 115
Publisher ID: TODJ-4-110
DOI: 10.2174/1874372201004010110
Article History:
Received Date: 11/06/2010Revision Received Date: 30/07/2010
Acceptance Date: 24/09/2010
Electronic publication date: 15/11/2010
Collection year: 2010
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Epiluminescence microscopy (ELM) is a non-invasive technique used to enhance visualization of microscopic structures of pigmented lesions for the early detection of melanoma. The 7-point check-list is a diagnostic method that requires the identification of only seven dermoscopic criteria, defining the image through the use of algorithms. This paper describes an experimental automated diagnosis set-up of melanocytic skin lesions through an image processing methodology focused on finding the presence of different epiluminescence parameters. In this paper the image processing set-up allows the automatic detection of some specific dermoscopic criteria. We analyze the blue whitish veil, the regression, and the irregular streaks. The procedure developed was tested by considering a set of about 200 ELM images. A good concordance between ELM 7-point checklist parameters detected and the new method of image processing was achieved by kappa analysis. Although ELM doesn’t substitute histological evaluation, it could be a reliable instrument to enhance clinical accuracy of skin pigmented lesions diagnosis.
