Department of Medical Physics, Mashhad University of Medical Science, Mashhad, Iran.
Department of Applied Mathematics, School of Mathematical Sciences, Ferdowsi University of Mashhad, Mashhad, Iran.
Iran J Basic Med Sci. 2013 Nov;16(11):1181-9.
OBJECTIVE(S): In SPECT, the sinogram contains scatter and lack of attenuated counts that degrade the reconstructed image quality and quantity. Many techniques for attenuation and scatter correction have been proposed. An acceptable method of correction is to incorporate effects into an iterative statistical reconstruction. Here, we propose new Maximum Likelihood Expectation Maximization (MLEM) formula to correct scattering and attenuating photons during reconstruction.
In this work, scatters are estimated through Klein-Nishina formula in all iterations and CT images are used for accurate attenuation correction. Reconstructed images resulted from different MLEM reconstruction formula have been compared considering profile agreement, contrast, mean square error, signal-to-noise ratio, contrast-to-noise ratio and computational time.
The proposed formula has a good profile agreement, increased contrast, signal-to-noise (SNR) & contrast-to-noise ratio (CNR), computational time and decreased mean square error (MSE) compared with uncorrected images and/or images from conventional formula.
In conclusion, by applying the proposed formula we were able to correct attenuation and scatter via MLEM and improve the image quality, which is a necessary step for both qualitative and quantitative SPECT images.
目的(S):在 SPECT 中,谱包含散射和缺乏衰减计数,这会降低重建图像的质量和数量。已经提出了许多衰减和散射校正技术。一种可接受的校正方法是将影响纳入迭代统计重建中。在这里,我们提出了新的最大似然期望最大化(MLEM)公式,以在重建过程中校正散射和衰减光子。
在这项工作中,通过克莱因-尼希纳公式在所有迭代中估计散射,并使用 CT 图像进行准确的衰减校正。考虑到轮廓一致性、对比度、均方误差、信噪比、对比噪声比和计算时间,比较了来自不同 MLEM 重建公式的重建图像。
与未校正图像和/或常规公式图像相比,该公式具有良好的轮廓一致性、对比度增加、信噪比(SNR)和对比噪声比(CNR)、计算时间减少和均方误差(MSE)减少。
总之,通过应用提出的公式,我们能够通过 MLEM 校正衰减和散射,并改善图像质量,这是定性和定量 SPECT 图像的必要步骤。