title: Anterior osteophyte discrimination in lumbar vertebrae using size-invariant features.
abstract: Radiologists often examine X-rays of cervical, thoracic and lumbar vertebrae for determining the presence of osteoarthritis and osteoporosis. For individual vertebra assessment, the boundary increasingly digresses from the general rectangular shape as the vertebra becomes less normal in appearance. For an abnormal vertebra, bony growths ('osteophytes') may appear at the vertebral comers, resulting in a change in the vertebra's shape. Image processing techniques are presented for computing size-invariant, convex hull-based features to highlight anterior osteophytes. Feature evaluation of 714 lumbar spine vertebrae using a multi-layer perceptron yielded normal and abnormal average correct discrimination of 90.5 and 86.6%, respectively.
authors.affiliation: Department of Electrical and Computer Engineering, University of Missouri-Rolla, 127 Emerson Electric Co. Hall, 1870 Miner Circle, Rolla, MO 65409-0040, USA.
authors.forename: Maruthi
authors.initials: M
authors.lastname: Cherukuri
authors.forename: R Joe
authors.initials: RJ
authors.lastname: Stanley
authors.forename: Rodney
authors.initials: R
authors.lastname: Long
authors.forename: Sameer
authors.initials: S
authors.lastname: Antani
authors.forename: George
authors.initials: G
authors.lastname: Thoma
mesh_terms: D000465:Algorithms; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008159:Lumbar Vertebrae / Q000000981:diagnostic imaging*; D016571:Neural Networks, Computer; D011859:Radiography; D013128:Spinal Osteophytosis / Q000000981:diagnostic imaging*