Diagnosis of malignant melanoma using a neural network

Author

Anurag Chawla

Abstract

"Malignant melanoma is the deadliest form of all skin cancers. Approximately 32,000 new cases of malignant melanoma were diagnosed in 1991, with approximately 80 percent of patients expected to survive five years [1], Fortunately, if detected early, even malignant melanoma may be treated successfully. Thus, in recent years, there has been a rising interest in the automated detection and diagnosis of skin cancer, particularly malignant melanoma [2]. In this thesis, a novel neural network approach for the automated distinction of melanoma from three benign categories of tumors which exhibit melanoma-like characteristics is presented. The approach is based on devising new and discriminant features which are used as inputs to an artificial neural network for classification of tumor images as malignant or benign. Promising results have been obtained using this method on real skin cancer images"--Abstract, page iii.

Advisor(s)

Erçal, Fikret

Committee Member(s)

Prater, John Bruce, 1932-2002
Moss, Randy Hays, 1953-

Department(s)

Computer Science

Degree Name

M.S. in Computer Science

Comments

A report which is substantially this thesis is available here for download.

Publisher

University of Missouri--Rolla

Publication Date

Fall 1993

Pagination

viii, 80 pages

Note about bibliography

Includes bibliographical references (pages 77-79).

Rights

© 1993 Anurag Chawla, All rights reserved.

Document Type

Thesis - Restricted Access

File Type

text

Language

English

Thesis Number

T 6660

Print OCLC #

30017232

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.

Recommended Citation

Chawla, Anurag, "Diagnosis of malignant melanoma using a neural network" (1993). Masters Theses. 1184.
https://scholarsmine.mst.edu/masters_theses/1184