一种自适应的CT图像联合代数重建算法

doi:10.3969/j.issn.1001-2400.2016.03.012

Abstract

Abstract:

The simultaneous algebraic reconstruction technique(SART) is a vintage algorithm for computed tomography(CT) image reconstruction, but it has many problems such as slow convergence speed, edge blur, and ringing effect. The relaxation parameter is an important factor affecting the performance of the algorithm, and we find that the edge region does not need the same relaxation factor as the uniform region, so an adaptive simultaneous algebraic reconstruction technique based on fuzzy entropy is proposed. After preliminary SART reconstruction, by quoting fuzzy entropy for edge detection of the reconstructed image which is used as prior information, a monotonous increasing function that defines the relaxation factor is constructed based on the neighborhoodhomogeneous measurement(NHM). Therefore, the proposed approach can select the relaxation factor adaptively by the local character of the image. Experimental results show that the new algorithm can solve the problem of edge blurring and suppress the ringing effect effectively in CT image reconstruction.

Key words: computed tomography, simultaneous algebraic reconstruction technique, fuzzy entropy, relaxation factor

QIAO Quanbang;HUANG Liyu;HE Zhijie. Image reconstruction using an adaptive simultaneous algebraic reconstruction technique in computed tomography[J].Journal of Xidian University, 2016, 43(3): 67-72.

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Image reconstruction using an adaptive simultaneous algebraic reconstruction technique in computed tomography

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