Masters Theses
Abstract
"The incidence of malignant melanoma, the deadliest skin cancer, has been rapidly rising. One of the key features that are used to discriminate malignant melanoma from nevi in dermoscopy skin lesion images is the presence of blotches, also called structureless areas. In this research, variations of blotch features developed in a previous study are investigated for discriminating malignant melanoma from nevi skin lesions. Absolute and relative color methods are explored to extract the blotchy areas from individual skin lesion images. Features are computed from the blotchy areas within each skin lesion image, including eccentricity measures, size of the blotches relative to the size of the skin lesion, irregularity index of the largest blotch, and dispersement index of the blotches. Using a neural network classifier, skin lesion discrimination results are compared for the different approaches for computing features from blotch regions in dermoscopy skin lesion images. The best diagnostic accuracy of 81.2% is achieved based on computing blotch features from blotchy areas determined using fuzzy logic techniques for three plane relative color and size"--Abstract, page iii.
Advisor(s)
Stanley, R. Joe
Committee Member(s)
Moss, Randy Hays, 1953-
Stoecker, William V.
Department(s)
Electrical and Computer Engineering
Degree Name
M.S. in Computer Engineering
Publisher
University of Missouri--Rolla
Publication Date
Summer 2006
Pagination
ix, 44 pages
Note about bibliography
Includes bibliographical references (pages 41-43).
Rights
© 2006 Azmath Ullah Khan, All rights reserved.
Document Type
Thesis - Restricted Access
File Type
text
Language
English
Subject Headings
Fuzzy logicMelanoma -- DiagnosisMoments of inertia -- MeasurementSkin -- Cancer -- Diagnosis
Thesis Number
T 9039
Print OCLC #
85776115
Recommended Citation
Khan, Azmath, "The extension of blotch features for melanoma discrimination in dermoscopy images" (2006). Masters Theses. 5932.
https://scholarsmine.mst.edu/masters_theses/5932
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