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Fast reconstruction with uniform noise properties in halfscan computed tomography
Author(s) -
Pan Xiaochuan
Publication year - 2000
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.1288239
Subject(s) - iterative reconstruction , noise (video) , algorithm , computer science , hybrid algorithm (constraint satisfaction) , reconstruction algorithm , hybrid system , tomography , artificial intelligence , computer vision , image (mathematics) , optics , physics , machine learning , constraint satisfaction , probabilistic logic , constraint logic programming
The hybrid algorithms developed recently for the reconstruction of fan‐beam images possess computational and noise properties superior to those of the fan‐beam filtered backprojection (FFBP) algorithm. However, the hybrid algorithms cannot be applied directly to a halfscan fan‐beam sinogram because they require knowledge of a fullscan fan‐beam sinogram. In this work, we developed halfscan‐hybrid algorithms for image reconstruction in halfscan computed tomography (CT). Numerical evaluation indicates that the proposed halfscan‐hybrid algorithms are computationally more efficient than are the widely used halfscan‐FFBP algorithms. Also, the results of quantitative studies demonstrated clearly that the noise levels in images reconstructed by use of the halfscan‐hybrid algorithm are generally lower and spatially more uniform than are those in images reconstructed by use of the halfscan‐FFBP algorithm. Such reduced and uniform image noise levels may be translated into improvement of the accuracy and precision of lesion detection and parameter estimation in noisy CT images without increasing the radiation dose to the patient. Therefore, the halfscan‐hybrid algorithms may have significant implication for image reconstruction in conventional and helical CT.