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- W2038026459 abstract "In this paper, a novel regularization approach for (non-statistical) iterative reconstruction is developed. In ourimplementation, the update equation of iterative reconstruction is based on Filtered Backprojection (FBP) and thesolution is stabilized using nonlinear regularization priors. It is well known that the usage of nonlinear regularizationpriors can reduce image noise at the same time preserving image sharpness [1]. The final noise level can be adjusted bydedicated choice of regularization priors, regularization strength and the total number of iterations. In contrast toconventional CT using convolution kernels, image characteristics can not be further manipulated. This might causeartificial image texture.We present a new class of (non-local) 3D-regularization priors, which gives us control over image characteristics similarto that obtained with conventional CT convolution kernels. In addition, efficient noise reduction at constant sharpness isobtained. Due to the manipulation of the low-frequency components of the regularization filter, the filter is non-local.The regularization strength becomes a 3D-matrix with contrast-dependent entries, which gives us control over contrastdependentsharpness. The contrast edges are estimated using a 3D Laplacian kernel. High contrast edges get a lowregularization weight and vice versa. We demonstrate the potential of noise reduction on basis of clinical CT data. Also,it is shown, that radiation exposure to the patient can be reduced by 60% in general purpose radiological CT applicationsand cardiac CT at the same time maintaining image quality. Moreover, for a 128-slice detector with 0.6 mm collimation,it is shown, that cone-beam and spiral artifacts caused by non-exact image reconstruction can be fairly removed. Puttingall together our iterative reconstruction approach substantially improves image quality in cone-beam CT, and thus hasthe potential to enter routine clinical CT." @default.
- W2038026459 created "2016-06-24" @default.
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- W2038026459 date "2010-03-04" @default.
- W2038026459 modified "2023-09-23" @default.
- W2038026459 title "Toward iterative reconstruction in clinical CT: increased sharpness-to-noise and significant dose reduction owing to a new class of regularization priors" @default.
- W2038026459 doi "https://doi.org/10.1117/12.844101" @default.
- W2038026459 hasPublicationYear "2010" @default.
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