Masters Theses

Abstract

"Approximately 40% of all cancers diagnosed in the United States are skin cancers[1]. Malignant melanoma is the most deadly form of skin cancer. This year there is a lifetime risk of developing melanoma 1 in 68, compared with the 1 in 150 lifetime risk reported in 1985[1]. Prevention, early diagnosis, and appropriate management are crucial to limiting this death toll.

The dermoscopic diagnosis of pigmented skin lesions is based on various analytic approaches or algorithms that have been set forth in the last few years, namely, pattern analysis, the ABCD rule [2,3] and the seven-point checklist [2,3] to quote but a few. The common denominator of all these diagnostic methods are particular dermoscopic features or, better, dermoscopic criteria that represent the backbone for the morphologic diagnosis of pigmented skin lesions.

In this thesis, the primary features of interest are areas of regression and granularity. Areas of regression are regions inside the tumor boundaries that exhibit low color variation. Granularity is a fine texture, which can be characterized as a highly localized noisy gray pixel pattern sometimes found close to areas of regression"-Abstract p. iii

Advisor(s)

Randy H. Moss

Committee Member(s)

R. Joe Stanley
William Van Stoecker

Department(s)

Electrical and Computer Engineering

Degree Name

M.S. in Computer Engineering

Publisher

University of Missouri--Rolla

Publication Date

Spring 2003

Pagination

viii, 56 pages

Note about bibliography

Includes bibliographical references (page 55)

Rights

© 2003 Sreenu Tatikonda, All rights reserved.

Document Type

Thesis - Restricted Access

File Type

text

Language

English

Subject Headings

Melanoma -- Diagnosis
Computer vision -- Technique -- Research

Thesis Number

T 8152

Print OCLC #

52640179

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