利用ITEM算法对ct数据进行三维图像重建

J. Durst, J. Pauli, G. Anton
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引用次数: 0

摘要

虚时间期望最大化(ITEM)是一种基于量子力学方法的通用最小化技术。它已被证明是一种有用的图像重建方法。ITEM是一种快速(与其他统计方法相比)和本质上3d友好(因为它对内存的要求低)的算法。因此,它是计算机断层扫描(CT)数据重建的一个很好的候选方法。作为一种统计方法,ITEM可以比过滤反投影(FB)等分析反投影方法更好地模拟成像系统的底层物理,从而可以在相同的数据集上获得更好的图像。本文介绍了ct数据的ITEM的两种实现以及两种方法所获得的结果图像。最后将结果与标准(FB)技术进行了比较。ITEM(算法以及它的所有实现)是在GNU/GPL条款下发布的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
3D image reconstruction of CT-data using the ITEM algorithm
ITEM (Imaginary Time Expectation Maximization) is a general minimization technique based on quantum-mechanical (QM)-methods. It has already proven to be a useful method for image reconstruction . ITEM is a fast (compared to other statistical methods) and intrinsically 3D-friendly (for its low demands on memory) algorithm. Therefore it is a good candidate for a reconstruction method for computed-tomography (CT)-data. Being a statistical method, it is possible with ITEM to model the underlying physics of the imaging system better than with an analytical backprojection method like filtered backprojection (FB) and so that better images with the same data set can be obtained. Two implementations of ITEM for CT-data and the resulting images achieved with both methods are presented. Finally the results are compared with standard (FB) techniques. ITEM (algorithm as well as all of its implementations) is published under the terms of GNU/GPL.
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