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A statistical method is developed to classify tissue types and to segment the corresponding tissue regions from relaxation time T(1 ), T(2), and proton density P(D) weighted magnetic resonance images. The method assumes that the distribution of image intensities associated with each tissue type can be expressed as a multivariate likelihood function of three(More)
Noise, partial volume (PV) effect, and image-intensity inhomogeneity render a challenging task for segmentation of brain magnetic resonance (MR) images. Most of the current MR image segmentation methods focus on only one or two of the above-mentioned effects. The objective of this paper is to propose a unified framework, based on the maximum a posteriori(More)
In this paper, we introduce a concise and concrete definition of an accurate colon centerline and provide an efficient automatic means to extract the centerline and its associated branches (caused by a forceful touching of colon and small bowel or a deep fold in twisted colon lumen). We further discuss its applications on fly-through path planning and(More)
We propose a novel multiscale penalized weighted least-squares (PWLS) method for restoration of low-dose computed tomography (CT) sinogram. The method utilizes wavelet transform for the multiscale or multi-resolution analysis on the sinogram. Specifically the Mallat-Zhong's wavelet transform is applied to decompose the sinogram to different resolution(More)
Reconstructing low-dose X-ray computed tomography (CT) images is a noise problem. This work investigated a penalized weighted least-squares (PWLS) approach to address this problem in two dimensions, where the WLS considers first- and second-order noise moments and the penalty models signal spatial correlations. Three different implementations were studied(More)
Electronic colon cleansing (ECC) aims to segment the colon lumen from a patient abdominal image acquired using an oral contrast agent for colonic material tagging, so that a virtual colon model can be constructed. Virtual colonoscopy (VC) provides fly-through navigation within the colon model, looking for polyps on the inner surface in a manner analogous to(More)
ÐVirtual endoscopy is a computerized, noninvasive procedure for detecting anomalies inside human organs. Several preliminary studies have demonstrated the benefits and effectiveness of this modality. Unfortunately, previous work cannot guarantee that an existing anomaly will be detected, especially for complex organs with multiple branches. In this paper,(More)
We present an interactive navigation system for virtual colonoscopy, which is based solely on high performance volume rendering. Previous colonic navigation systems have employed either a surface rendering or a Z-buffer-assisted volume rendering method that depends on the surface rendering results. Our method is a fast direct volume rendering technique that(More)
30 virtual colonoscopy has recently beenproposed as a non-invasive alternativeprocedure for the visualization of the human colon, Su@ace rendering is sujicientfor implementing such a procedure to obtain an overview of the interior surface of the colon at interactive rendering speeds. Unfortunately , physicians can not use it to explore tissues beneath the(More)
A mathematical method was studied to model the detector response of high spatial-resolution positron emission tomography systems consisting of close-packed small crystals, and to restore the resolution deteriorated due to crystal penetration and/or nonuniform sampling across the field-of-view (FOV). The simulated detector system had 600 bismuth germanate(More)