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Proceedings Paper

Vertebral segmentation using contourlet-based salient point matching and localized multiscale shape prior
Author(s): R. Zewail; A. Elsafi; N. Durdle
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Paper Abstract

Medical experts often examine hundreds of spine x-rays to determine existence of diseases like osteoarthritis, osteoporoses, and osteophites. Accurate vertebrae segmentation plays a great role in the proper assessment of various vertebral abnormalities. Manual segmentation methods are both time consuming and non-reproducible, hence, developing efficient computer-assisted segmentation methods has been a long standing goal. Over the past decade, segmentation methods that utilize statistical models of shape and appearance have drawn much interest within the medical imaging community. However, despite being a promising approach, they are always faced with a number of challenges such as: poor image quality, and the ability to generalize well to unseen vertebral deformities. This paper presents a novel vertebral segmentation method using Contourlet-based salient point matching and a localized multi-scale shape prior. We employ a multi-scale directional analysis tool, namely contourlets, to build local appearance profiles at salient points of the vertebra's body. The contourlet-based local appearance model is used to detect the vertebral bodies in the test x-ray image. A novel localized multi-scale shape prior is used to drive the segmentation process. Within a best-basis selection framework, the proposed shape prior benefits from the multi-scale nature of wavelet packets, and the capability of ICA to capture hidden independent modes of variations. Experiments were conducted using a set of 100 digital x-ray images of lumbar spines. The contourlet-based appearance profiles and the localized multi-scale shape prior were constructed using a training subset of images, and then matched to unseen images. Promising results were obtained compared to related work in the literature with an average segmentation error of 1.1997 mm.

Paper Details

Date Published: 27 March 2009
PDF: 9 pages
Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 72594Z (27 March 2009); doi: 10.1117/12.812729
Show Author Affiliations
R. Zewail, Univ. of Alberta (Canada)
A. Elsafi, Univ. of Alberta (Canada)
N. Durdle, Univ. of Alberta (Canada)


Published in SPIE Proceedings Vol. 7259:
Medical Imaging 2009: Image Processing
Josien P. W. Pluim; Benoit M. Dawant, Editor(s)

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