IMAGE PROCESSING UNDER EDGE DETECTION AND CORRECTION ALGORITHM FOR 3D CT IMAGES
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ABSTRACT: The normal direction of the bone contour in computed tomography (CT) images provides important anatomical information and can guide segmentation algorithms. Since various bones in CT images have different sizes, and the intensity values of bone pixels are generally nonuniform and noisy, estimation of the normal direction using a single scale is not reliable. We propose a multiscale approach to estimate the normal direction of bone edges. The reliability of the estimation is calculated from the estimated results and, after re-scaling, the reliability is used to further correct the normal direction. The optimal scale at each point is obtained while estimating the normal direction; this scale is then used in a simple edge detector. The reliability may become more stable from slice to slice when we use 3-D information to estimate the normal direction of bone edges. Thus, it is expected that the 3-D extension will shorten the segmentation time and improve the performance.
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