Masters Theses

Abstract

“Melanoma is a form of a skin cancer that can be deadly if not treated in the early stages. Imaging of skin lesions provides an important diagnostic aid to dermatologists in the detection of malignant melanoma. There are several important features used for detecting melanoma, including lesion asymmetry, border irregularity, color variegation and skin lesion diameter. It is believed that color plays an important role in the diagnosis of malignant melanoma. There are “melanoma colors” lying in the color space. Color variegation usually involves examining skin lesions for certain colors or groups of colors that are indicative of melanoma. An alternative approach to melanoma detection is to identify colors that are most characteristic of benign lesions and to evaluate skin lesion color deviation with those characteristic colors. Accordingly, a perception-based framework provides the capability to make quantitative assessments related to the degree of similarity of skin lesions to benign lesion standards. In this research, a fuzzy logic- based approach for skin lesion color analysis is investigated for differentiating benign skin lesions from melanomas in dermatology clinical images. Experimental results are reported over a data set of 258 clinical images, including 129 benign lesions and 129 melanomas. Two different membership functions, stepwise and trapezoidal, are used in order to represent the fuzzy sets. A fusion approach is presented of the trapezoidal membership function-based approach with an existing skin lesion percent melanoma color feature for enhanced skin lesion classification”--Abstract, page iii.

Advisor(s)

Stanley, R. Joe

Committee Member(s)

Moss, Randy Hays, 1953-
St. Clair, Daniel C.

Department(s)

Electrical and Computer Engineering

Degree Name

M.S. in Computer Engineering

Publisher

University of Missouri--Rolla

Publication Date

Summer 2002

Pagination

viii, 47 pages

Note about bibliography

Includes bibliographical references (pages 45-46).

Rights

© 2002 Chetna Vidyasagar Aggarwal, All rights reserved.

Document Type

Thesis - Restricted Access

File Type

text

Language

English

Subject Headings

Melanoma -- Diagnosis
Melanoma -- Classification -- Research

Thesis Number

T 8109

Print OCLC #

52597611

Link to Catalog Record

Electronic access to the full-text of this document is restricted to Missouri S&T users. Otherwise, request this publication directly from Missouri S&T Library or contact your local library.

http://merlin.lib.umsystem.edu/record=b4970280~S5

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