Masters Theses

Keywords and Phrases

Live wire segmentation tool; Osteophytes

Abstract

"Computer-assisted image segmentation can be a challenging problem. In previous research, manual segmentation was used for the detection of key features in cervical and lumbar x-ray images. In this research, a semi-automated live wire technique is investigated and is evaluated for the detection of anterior osteophytes in lumbar vertebrae. Convex hull-based features are extracted from manual and live wire segmented vertebrae for anterior osteophyte discrimination over 405 lumbar vertebrae, 204 abnormal vertebrae with anterior osteophytes and 201 normal vertebrae. A leave-one-out standard back propagation neural network was used for vertebrae classification. Experimental results show that manual segmentation yielded slightly better discrimination results than the live wire technique."--Abstract, page iii.

Advisor(s)

Stanley, R. Joe

Committee Member(s)

Moss, Randy Hays, 1953-
Agarwal, Sanjeev, 1971-

Department(s)

Electrical and Computer Engineering

Degree Name

M.S. in Electrical Engineering

Publisher

University of Missouri--Rolla

Publication Date

Fall 2004

Pagination

viii, 40 pages

Note about bibliography

Includes bibliographical references (pages 38-39).

Rights

© 2004 Suren Eda Naarayana Kulothungan, All rights reserved.

Document Type

Thesis - Restricted Access

File Type

text

Language

English

Subject Headings

Osteoarthritis -- Diagnosis -- ResearchLumbar vertebrae -- ImagingComputer vision in medicineImage analysis

Thesis Number

T 8673

Print OCLC #

62349672

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