Masters Theses

Hsi-Chieh Lee

Abstract

"Skin cancer, the most common cancer in the United States that affects about 600,000 Americans every year, accounts for 1 % of all cancer deaths. Among all, Malignant Melanoma is the most virulent form of skin cancer that is responsible for 75% of all deaths from skin cancer. In 1992, approximately 32,000 people are expected to develop melanoma and about 6,700 will die. However, even malignant melanoma can be treated successfully if detected in the early phase. Therefore, our research goal is to diagnose skin cancer, especially malignant melanoma.

In this study, only the digitized images obtained from color tumor slides are used for the diagnosis. Image processing techniques, neural network system, and fuzzy inference system are combined here to diagnose skin cancer. The output yielded by the image processing techniques is served as the input to the proposed integrated systems. There are two integrated systems developed in this study. In system I, a rulebased pre-screener and a multi-layer perceptron with the backpropagation learning algorithm are combined for the diagnosis. In system II, a hierarchical diagnostic-tree based neural network system is developed which integrates a fuzzy inference system to improve the diagnostic accuracy. The results are also compared to those obtained by the dermatologists, which demonstrates the diagnostic capability of the proposed systems"--Abstract, p. iii

Advisor(s)

Ercal, Fikret

Committee Member(s)

Zobrist, George W. (George Winston), 1934-
Dagli, Cihan H., 1949-

Department(s)

Computer Science

Degree Name

M.S. in Computer Science

Publisher

University of Missouri--Rolla

Publication Date

Spring 1994

Pagination

viii, 103 pages

Note about bibliography

Includes bibliographical references (pages 99-102)

Rights

© 1994 Hsi-Chieh Lee, All rights reserved.

Document Type

Thesis - Open Access

File Type

text

Language

English

Thesis Number

T 6786

Print OCLC #

31065142

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