Masters Theses

Author

Azmath Khan

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 logic
Melanoma -- Diagnosis
Moments of inertia -- Measurement
Skin -- Cancer -- Diagnosis

Thesis Number

T 9039

Print OCLC #

85776115

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=b5792741~S5

Share My Thesis If you are the author of this work and would like to grant permission to make it openly accessible to all, please click the button above.

Share

 
COinS