Masters Theses
Abstract
“Radiologists often examine x-rays of cervical, thoracic and lumbar vertebrae for determining the presence of osteoarthritis and osteoporosis. There are several features used to assess whether a vertebra is normal such as the height contrast in the anterior and posterior sides. Vertebral distortion along the anterior boundary can also be used as an indicator of vertebra normality. The vertebral boundary increasingly deviates from the general rectangular shape as the vertebra becomes less normal in appearance. For abnormal vertebrae, bony growths (“osteophytes”) may appear at the vertebral comers. This research introduces image processing techniques for computing size-invariant features from lumbar spine vertebrae for detecting anterior osteophytes. Four size invariant features based on the vertebral convex hull are investigated for highlighting anterior osteophytes to differentiate normal from abnormal vertebrae. A multi-layer perceptron-based approach is used for feature evaluation of 714 lumbar spine vertebrae. Experimental results yield an average correct recognition of 90.5% of abnormal vertebrae and 86.6% correct normal vertebrae classification."--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
Fall 2003
Pagination
vii, 27 pages
Note about bibliography
Includes bibliographical references (pages 24-26).
Rights
© 2003 Maruthi Cherukuri, All rights reserved.
Document Type
Thesis - Restricted Access
File Type
text
Language
English
Subject Headings
Computer vision in medicineImage analysisOsteoarthritis -- Diagnosis -- Research
Thesis Number
T 8299
Print OCLC #
54799767
Recommended Citation
Cherukuri, Maruthi, "Anterior osteophyte detection in lumbar vertebrae using size-invariant features" (2003). Masters Theses. 2366.
https://scholarsmine.mst.edu/masters_theses/2366
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