Automatic recognition of bone for x-ray bone densitometry

Larry A. Shepp; Y. Vardi; J. Lazewatsky; James Libeau; Jay A. Stein

doi:10.1117/12.45385

1 June 1991 Automatic recognition of bone for x-ray bone densitometry

Larry A. Shepp, Y. Vardi, J. Lazewatsky, James Libeau, Jay A. Stein

Proceedings Volume 1452, Image Processing Algorithms and Techniques II; (1991) https://doi.org/10.1117/12.45385
Event: Electronic Imaging '91, 1991, San Jose, CA, United States

Abstract

We described a method for automatically identifying and separating pixels representing bone from those representing soft tissue in a dual- energy point-scanned projection radiograph of the abdomen. In order to achieve stable quantitative measurement of projected bone mineral density, a calibration using sample bone in regions containing only soft tissue must be performed. In addition, the projected area of bone must be measured. We show that, using an image with a realistically low noise, the histogram of pixel values exhibits a well-defined peak corresponding to the soft tissue region. A threshold at a fixed multiple of the calibration segment value readily separates bone from soft tissue in a wide variety of patient studies. Our technique, which is employed in the Hologic QDR-1000 Bone Densitometer, is rapid, robust, and significantly simpler than a conventional artificial intelligence approach using edge-detection to define objects and expert systems to recognize them.

Citation Download Citation

Larry A. Shepp, Y. Vardi, J. Lazewatsky, James Libeau, and Jay A. Stein "Automatic recognition of bone for x-ray bone densitometry", Proc. SPIE 1452, Image Processing Algorithms and Techniques II, (1 June 1991); https://doi.org/10.1117/12.45385

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