Variable Weighted Ordered Subset Image Reconstruction Algorithm
نویسندگان
چکیده
منابع مشابه
Variable Weighted Ordered Subset Image Reconstruction Algorithm
We propose two variable weighted iterative reconstruction algorithms (VW-ART and VW-OS-SART) to improve the algebraic reconstruction technique (ART) and simultaneous algebraic reconstruction technique (SART) and establish their convergence. In the two algorithms, the weighting varies with the geometrical direction of the ray. Experimental results with both numerical simulation and real CT data ...
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The expectation-maximization (EM) algorithm for maximum-likelihood image recovery is guaranteed to converge, but it converges slowly. Its ordered-subset version (OS-EM) is used widely in tomographic image reconstruction because of its order-of-magnitude acceleration compared with the EM algorithm, but it does not guarantee convergence. Recently the ordered-subset, separable-paraboloidal-surroga...
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OBJECTIVES We observed whether clearer tumor delineation and greater tumor to non-tumor (T/N) count ratios could be obtained using an iterative ordered-subsets expectation maximization (OSEM) algorithm than conventional filtered-back projection algorithm (FBP) in the image reconstruction of thallium-201 (201Tl) lung scintigraphy. METHODS In 29 patients with lung cancer and phantom studies, to...
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Statistical image reconstruction methods improve image quality in X-ray CT, but long compute times are a drawback. Ordered subsets (OS) algorithms can accelerate convergence in the early iterations (by a factor of about the number of subsets) provided suitable “subset balance” conditions hold. OS algorithms are most effective when a properly scaled gradient of each subset data-fit term can appr...
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ژورنال
عنوان ژورنال: International Journal of Biomedical Imaging
سال: 2006
ISSN: 1687-4188,1687-4196
DOI: 10.1155/ijbi/2006/10398