Masters Theses

Keywords and Phrases

Acetowhite

Abstract

"Cervical cancer is the second most common type of cancer that prevails among women. The death rate due to cervical cancer in developing countries is much more than developed countries due to the lack of trained personnel. This thesis discusses techniques investigated to create a fully automated system that aids in detecting cancer. Image matching techniques helps in pairing similar images in the database. Computer-based tools are developed that process the images for enhancement due to conditions such as lighting, and which extract and analyse key features of the cervix. A very efficient algorithm for segmentation of acetowhite regions is developed. A diagnostic accuracy of 93 % is achieved using neighboring gray level dependence matrix texture features and a neural network classification scheme"--Abstract, page iii.

Advisor(s)

Stanley, R. Joe

Committee Member(s)

Stoecker, William V.
Moss, Randy Hays, 1953-

Department(s)

Electrical and Computer Engineering

Degree Name

M.S. in Computer Engineering

Publisher

University of Missouri--Rolla

Publication Date

Fall 2006

Pagination

viii, 59 pages

Note about bibliography

Includes bibliographical references (pages 56-58)

Rights

© 2006 Shoba Umamaheswaran, All rights reserved.

Document Type

Thesis - Restricted Access

File Type

text

Language

English

Subject Headings

Cervix uteri -- Cancer -- Diagnosis Image analysis Pattern recognition systems

Thesis Number

T 9078

Print OCLC #

123568957

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