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Melanoma Decision Support System for Dermatologist

Published on March 2012 by Priya Shetty, Varsha Turkar
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International Conference on Recent Trends in Information Technology and Computer Science
Foundation of Computer Science USA
ICRTITCS - Number 2
March 2012
Authors: Priya Shetty, Varsha Turkar
04234d54-a1d7-4eab-b5e2-b829b293e9e1

Priya Shetty, Varsha Turkar . Melanoma Decision Support System for Dermatologist. International Conference on Recent Trends in Information Technology and Computer Science. ICRTITCS, 2 (March 2012), 28-30.

@article{
author = { Priya Shetty, Varsha Turkar },
title = { Melanoma Decision Support System for Dermatologist },
journal = { International Conference on Recent Trends in Information Technology and Computer Science },
issue_date = { March 2012 },
volume = { ICRTITCS },
number = { 2 },
month = { March },
year = { 2012 },
issn = 0975-8887,
pages = { 28-30 },
numpages = 3,
url = { /proceedings/icrtitcs/number2/5182-1014/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Recent Trends in Information Technology and Computer Science
%A Priya Shetty
%A Varsha Turkar
%T Melanoma Decision Support System for Dermatologist
%J International Conference on Recent Trends in Information Technology and Computer Science
%@ 0975-8887
%V ICRTITCS
%N 2
%P 28-30
%D 2012
%I International Journal of Computer Applications
Abstract

Malignant melanoma is nowadays one of the leading cancers among many white-skinned populations around the world. Malignant melanoma, the most deadly form of skin cancer, has a good prognosis if treated in the curable early stages. Early diagnosis is the most effective treatment of melanoma. Well-trained dermatologists reach a high level of diagnostic accuracy but their performance is increased by using computer aided numerical imaging tools. This study is limited in the use of simple image processing algorithms, for the sake of clarity, in order to illustrate the use of MATLAB in the calculation of the ABCD Total Dermatoscopy Score (TDS) for potentially malignant melanomas. A high ABCD score means that a lesion is more likely to be a malignant melanoma.

References
  1. Stolz W, Riemann A, Cognetta AB. ABCD rule of dermatoscopy: a new practical method for early recognition of malignant melanoma. Eur J Deratol 1994; 4:521-7
  2. G. Argenziano, C. Catricala, M. Ardigo, P. Buccini, P. De Simone, L. Eibenschutz, A. Ferrari, G. Mariani, V. Silipo, I. Sperduti, I. Zalaudek. Seven-point Checklist of Dermoscopy Revisited. The British Journal of Dermatology 2011; 164(4):785-790
  3. Parkin D, Bray F, Ferlay J, Pisani P. Global
  4. Otsu N. A Threshold Selection Method from Gray-Level Histograms. IEEE Transactions on Systems, Man, and Cybernetics. 1979. Vol. 9 Issue 1:62-66.
  5. Schmid-Saugeon P, Guillod J, Thiran JP. Towards a computer-aided diagnosis system for pigmented skin lesions. Computerized Medical Imaging and Graphics 2003. 27(1);65-78
Index Terms

Computer Science
Information Sciences

Keywords

Melanoma benign suspicious malignant ABCD Matlab Dermatoscopy image processing