Regularization based simultaneous algebraic reconstruction techniques for computed tomography

Shailendra Tiwari, Deepikanshu Chouksey, Vinod Todwal
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引用次数: 1

Abstract

Simultaneous algebraic reconstruction Technique(SART) based iterative method play a major role in the quality of images reconstructed by Computed Tomography (CT). The basic limitations associated with this method include poor visual quality and ill-posedness. To address these drawbacks, SART iterative method is modified using Anisotropic Diffusion (AD) as regularization prior to tackle with ill-posedness as well as visual quality issue. To evaluate the proposed method, both qualitative and quan­titative studies were conducted and results were compared with existing methods using two different simulated test phantoms. Experimental results show that the proposed model yields significant gain in terms of visual reconstructed image quality and noise suppression.
基于正则化的计算机断层扫描同步代数重建技术
基于同步代数重建技术(SART)的迭代方法对计算机断层扫描(CT)图像的重建质量起着重要的作用。与这种方法相关的基本限制包括视觉质量差和姿势不佳。为了解决这些问题,采用各向异性扩散(AD)作为正则化,改进了SART迭代方法,从而解决了不适定性和视觉质量问题。为了评估所提出的方法,进行了定性和定量研究,并使用两种不同的模拟测试模型将结果与现有方法进行了比较。实验结果表明,该模型在视觉重构图像质量和噪声抑制方面均有显著提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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