Automatic Classification System for Lumbar Spine X-ray Images

  • Authors:
  • Soontharee Koompairojn;Kien A. Hua;Chutima Bhadrakom

  • Affiliations:
  • University of Central Florida, USA;University of Central Florida, USA;Thai Nakarin Hospital, Thailand

  • Venue:
  • CBMS '06 Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems
  • Year:
  • 2006

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Abstract

Existing computer-based spinal stenosis diagnosis systems are not fully automatic. Their performance depends on the knowledge and experience of the user. Such a system is typically intended for specialists such as radiologists. We present in this paper a fully automatic system, more suitable for general practitioners for use in screening and initial diagnosis. To evaluate the performance of the proposed techniques, we build a system prototype with two environments -one for managing training images and building the classifiers, and the other environment for diagnosis use in practice. Our experimental results, based on an X-ray image database NHANES II available from the National Library of Medicine, indicates that the proposed system is effective for screening purpos