Masters Theses

Abstract

“Basal cell carcinoma (BCC) is one of the most common types of skin cancer in the United States. Early detection of BCC by noninvasive techniques can decrease delay in treatment and save cost. A recent study estimated that 5.4 million cases of non-melanocytic skin cancer (NMSC) occur each year in the US. BCC accounts for 50% of NMSC cases. Telangiectasia, which appears in most BCCs is an important feature for identification of BCC for an automatic diagnostic system. In this thesis, three methods for detection of telangiectasia present in dermoscopy lesion image (DI) were proposed. Detected telangiectasia in DI was used to predict BCC. Using stepwise logistic regression, a model was created for which the area under a receiver operating characteristic (ROC) curve of 88.9% was achieved for detection of BCC”--Abstract, page iii.

Advisor(s)

Moss, Randy Hays, 1953-

Committee Member(s)

Stanley, R. Joe
Shrestha, Bijaya

Department(s)

Electrical and Computer Engineering

Degree Name

M.S. in Electrical Engineering

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2017

Pagination

xiii, 49 pages

Note about bibliography

Includes bibliographic references (page 48).

Rights

© 2017 Hemanth Yadav Aradhyula, All rights reserved.

Document Type

Thesis - Open Access

File Type

text

Language

English

Thesis Number

T 11999

Electronic OCLC #

1313117320

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