Masters Theses


“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.


Stanley, R. Joe

Committee Member(s)

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


Electrical and Computer Engineering

Degree Name

M.S. in Computer Engineering


University of Missouri--Rolla

Publication Date

Fall 2003


vii, 27 pages

Note about bibliography

Includes bibliographical references (pages 24-26).


© 2003 Maruthi Cherukuri, All rights reserved.

Document Type

Thesis - Restricted Access

File Type




Subject Headings

Computer vision in medicine
Image analysis
Osteoarthritis -- Diagnosis -- Research

Thesis Number

T 8299

Print OCLC #


Link to Catalog Record

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