27 March 2009 Vertebral segmentation using contourlet-based salient point matching and localized multiscale shape prior
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Proceedings Volume 7259, Medical Imaging 2009: Image Processing; 72594Z (2009) https://doi.org/10.1117/12.812729
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States
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.
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R. Zewail, R. Zewail, A. Elsafi, A. Elsafi, N. Durdle, N. Durdle, "Vertebral segmentation using contourlet-based salient point matching and localized multiscale shape prior", Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 72594Z (27 March 2009); doi: 10.1117/12.812729; https://doi.org/10.1117/12.812729

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