Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Rajab, Maher I.
Affiliations: Computer Engineering Department, University of Umm Al-Qura, P.O. Box 5555, Mecca, Kingdom of Saudi Arabia
Note: [] Corresponding author. E-mail: Rajabmah@uqu.edu.sa
Abstract: Since the introduction of epiluminescence microscopy (ELM), image analysis tools have been extended to the field of dermatology, as an attempt to algorithmically reproduce clinical evaluation. Accurate image segmentation of skin lesions is one of the key steps for useful, early, and non-invasive diagnosis of coetaneous melanomas. This paper proposes an image segmentation algorithm to extract the true border that reveals the global structure irregularity (indentations and protrusions), which may suggest excessive cell growth or regression of a melanoma. The algorithm is applied to the blue channel of the RGB colour vectors to distinguish lesions from the skin and. Analysis of image background is applied by recursive measure of the median and standard deviation of background. This will facilitate automatic and recurring noise reduction and enhancement by image pre-processing. The algorithm also does not depend on the use of rigid threshold values, because an optimal thresholding algorithm "isodata algorithm" that is used determines an optimal threshold iteratively. Experiments are performed on diversity of synthetic skin images that model real hair and lesions of different border irregularities. The aim is to verify the capability of the segmentation algorithm in extracting and characterizing the true features of the processed skin lesions. The next phase of test applies the algorithm to real skin lesions representing high resolution ELM images. We demonstrate that we can enhance and delineate pigmented networks in skin lesions visually, and make them accessible for further analysis and classification.
Keywords: Epiluminescence microscopy, skin lesion, optimal thresholding, image segmentation, SIAscope images
Journal: Journal of X-Ray Science and Technology, vol. 16, no. 1, pp. 33-42, 2008
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl