SPECT 最大似然重建的评估。

An evaluation of maximum likelihood reconstruction for SPECT.

机构信息

Dept. of Electr. Eng., Washington Univ., St. Louis, MO.

出版信息

IEEE Trans Med Imaging. 1990;9(1):99-110. doi: 10.1109/42.52987.

Abstract

A reconstruction method for SPECT (single photon emission computerized tomography) that uses the maximum likelihood (ML) criterion and an iterative expectation-maximization (EM) algorithm solution is examined. The method is based on a model that incorporates the physical effects of photon statistics, nonuniform photon attenuation, and a camera-dependent point-spread response function. Reconstructions from simulation experiments are presented which illustrate the ability of the ML algorithm to correct for attenuation and point-spread. Standard filtered backprojection method reconstructions, using experimental and simulated data, are included for reference. Three studies were designed to focus on the effects of noise and point-spread, on the effect of nonuniform attenuation, and on the combined effects of all three. The last study uses a chest phantom and simulates Tl-201 imaging of the myocardium. A quantitative analysis of the reconstructed images is used to support the conclusion that the ML algorithm produces reconstructions that exhibit improved signal-to-noise ratios, improved image resolution, and image quantifiability.

摘要

一种使用最大似然（ML）准则和迭代期望最大化（EM）算法求解的 SPECT（单光子发射计算机断层扫描）重建方法进行了研究。该方法基于一个模型，该模型结合了光子统计、非均匀光子衰减和相机相关点扩散响应函数的物理效应。从模拟实验中给出了重建结果，说明了 ML 算法校正衰减和点扩散的能力。为了参考，还包括了使用实验和模拟数据的标准滤波后向投影方法重建。进行了三项研究，重点研究了噪声和点扩散的影响、非均匀衰减的影响以及这三个因素的综合影响。最后一项研究使用胸部模型并模拟 Tl-201 心肌成像。对重建图像进行了定量分析，支持了这样的结论，即 ML 算法产生的重建图像具有更高的信噪比、更高的图像分辨率和更好的图像可量化性。