Article

Reconstruction of Region-of-interest Image in Narrow-field-of-view Computed Tomography without Prior Constraints

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Abstract

This paper presents a numerical method for reconstructing a tomographic image for a region of interest (RoI) within a section using narrowed radiation beams to reduce radiation exposure. The RoI image reconstruction is formulated as a discrete problem to avoid the truncated (incomplete) problem associated with the conventional analytic filtered backprojection method. This in turn allows local reconstruction of RoI images without any prior information or constraints. A coarse image of the entire section is first reconstructed with the aid of a modified convex maximum likelihood (MCML) algorithm. The coarse image is then used to account for the effect of the RoI surroundings. With RoI-specific projections, an RoI image is then reconstructed, with either the MCML or conjugate gradient methods, at the desired pixel size. The proposed method is evaluated using an anthropomorphic FORBILD head phantom, showing an image quality comparable to that of conventional computed tomography, but with a ∼69% reduction in radiation exposure. Unlike existing approaches that require some prior knowledge of a segment of the image, this approach does not require any prior image information and imposes no constraints on the solution.

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... To be able to use a visualization for diagnosis, surgery planning, or precise quantitative measurements, the anatomical structure(s) of interest should be segmented [14,15] using appropriate tools [12,[16][17][18]. As computer-aided systems evolve rapidly, the need for parameterization of complex methods [19][20][21] has become more important. Pre-processing of the volume data aims to improve the segmentation process (i.e., data reduction, noise suppression). ...
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The quality of pictures which are generated by X-ray scanners is limited essentially by the inter-dependence of patient dose, contrast and spatial resolution. When the collection of scan data is restricted to a region of medical interest, the skin dose can be reduced or the resolution can be improved. Two methods are presented which produce excellent pictures of the region from restricted scan data to be collected by a rotation-only scanner. The first method, SVIS, makes use of additional data outside the region, which are scanned at an X-ray intensity which is reduced by means of an absorber in front of the X-ray tube. The second method, SRACS, requires no X-ray data outside the region and replaces the missing data by artificial data which are calculated from the slice outline. This is determined by optical means. Pictures are shown which are reconstructed from true scan data of a body slice, where the data restriction is simulated on a computer and the Convolution method is used as the reconstruction technique.
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A generalized method for the reconstruction of a region of interest within a slice in the presence of beam hardening is introduced. The method, limited field of reconstruction (LFV), is based on variable sampling of the projection data and a post-reconstruction correction scheme. An initial reconstruction of the whole slice is performed using the coarsely sampled projections. The low resolution reconstructed image is used to estimate the bone and tissue thicknesses along each ray. The bone and tissue lengths obtained from the first low resolution image are then used in subtracting the contribution of the external region from the region of interest and to correct for beam hardening. The finely sampled corrected projections are used in reconstructing a high resolution image of the region of interest without artifacts from the external region and beam hardening. Computer simulation results are presented and applicability of the present correction method to practical scanners is discussed.
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