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Lookup NU author(s): Dr Muhammad Azad
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© 2017 IEEE. Melanoma is the most deadly form of skin cancer and its incidence rate is significantly increasing. The design of an assisted diagnosis system for the detection of melanoma is a challenging task involving various steps related to computer vision. Researchers have concluded that the accurate identification of melanoma requires robust preprocessing steps on dermoscopy images including hair removal, illumination correction etc., that can help in a better detection of melanoma. In this paper, we propose a novel illumination correction algorithm followed by robust feature extraction from dermoscopy images, leading to a better identification of cancer. Illumination correction is based on statistical estimation of illumination content in the images, followed by the extraction of differential structures using a combination of Gabor filtering followed by extracting local mesh patterns, which exhibit physiological significance based on various clinical rules for detecting melanoma. Our experiments show that the proposed technique outperforms all the other methods that have been considered in this paper.
Author(s): Riaz F, Nisar R, Hassan A, Sakeena M, Azad MA
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: 2017 International Conference on Computational Science and Computational Intelligence (CSCI)
Year of Conference: 2018
Pages: 426-431
Online publication date: 06/12/2018
Acceptance date: 02/04/2016
Publisher: Institute of Electrical and Electronics Engineers Inc.
URL: https://doi.org/10.1109/CSCI.2017.72
DOI: 10.1109/CSCI.2017.72
Library holdings: Search Newcastle University Library for this item
ISBN: 9781538626528