SPECT图像解析重建算法研究现状

单光子发射断层成像(SPECT)在临床上有广泛的应用,但由于各种因素的限制,一般仅能得到定性成像,大大削弱了其诊断功能。要想得到定量的图像,就需要在图像重建过程中对各种影响因素进行补偿。目前所用重建算法主要分为迭代法和解析法两大类。本文主要阐述用于SPECT图像重建的各种解析算法,通过追踪国际研究前沿,对现有算法按噪声抑制、散射去除、衰减校正、探测器效应补偿等分类进行了较为全面的概述。

Analytical Algorithms Improving the Reconstruction of SPECT Image

Single photon emission computed tomography (SPECT) is a cost-effective, widely-used diagnostic modality for the assessment of cardiac and cerebral functions. However, most SPECT protocols for clinical use support only qualitative reconstruction. Its lack of quantitative capability compromises the accurate evaluation of diseases. Quantitative SPECT by simultaneous compensation for different degradation factors is in great demand and should improve the diagnosis greatly. The variety of the existing SPECT algorithm can be split into a family of analytical methods and a wide class of iterative techniques. By reviewing the research work published in the past decades, this paper tries to make a state of arts and comprehensive outline of efficient, analytical solutions to SPECT reconstruction problem, which could compensate scatter, photon attenuation, and detector response, as well as suppression of Poisson noise, respectively.