首页> 外文会议>IEEE Nuclear Science Symposium >Quantitative image reconstruction in simultaneous /sup 123/I//sup 99m/Tc myocardial SPECT
【24h】

Quantitative image reconstruction in simultaneous /sup 123/I//sup 99m/Tc myocardial SPECT

机译:同时/ SUP 123 / I // SUP 99M / TC心肌SPECT的定量图像重建

获取原文

摘要

In the /sup 123/I//sup 99m/Tc myocardial SPECT study the image reconstructed with the counts of primary photons emitted from the low photopeak energy (/sup 99m/Tc) radionuclide is distorted by Compton scattered photons originating in the high photopeak energy (/sup 123/I) radionuclide. To correct the scattered photons included in the low energy photopeak window in the simultaneous data acquisition, we proposed a method with a neural network at the IEEE MIC in 1999. This method uses a layered neural network (input units: 10, hidden units: 20 and output units: 2). El Fakhri et al. (2001) also proposed a method at the IEEE MIC in 1999 which was like our approach, and they obtained good results. The major differences between their method and ours are (1) the energy range for data acquisition, (2) the width of the narrow energy window, and (3) the method for calculating the number of primary photons. This paper investigates the performance of their method and ours in consideration of the above three points. Performance was evaluated with Monte Carlo simulation data and experiment data. In the simulation we used the MCAT phantom and accuracy was evaluated by the mean squared error in the reconstructed images. The results indicated that the accuracy of our method was slightly superior to El Fakhri's method. In the experiment we fixed the energy range to 120-180 keV and changed the width of the narrow energy window to 2.2, 4.4 and 6.7 keV. The results showed that a window width of 2.2 keV was too narrow for as an energy window. In conclusion, it was confirmed that our method was slightly superior to El Fakhri's method and both methods were fairly effective in separating /sup 99m/Tc and /sup 123/I accurately.
机译:在/ sup 123 / i // sup 99m / tc心肌spect研究中,用从低位光辐射能量(/ sup 99m / tc)放射核素发射的初级光子的计数重建的图像通过源自高photopak的Compton散射光子扭曲能量(/ sup 123 / i)放射​​性核素。为了在同时数据采集中校正低能量PhotoPeak窗口中包括的散射光子,我们在1999年提出了一种在IEEE MIC上的神经网络的方法。该方法使用分层神经网络(输入单元:10,隐藏单元:20和输出单位:2)。 el fakhri等。 (2001)还提出了1999年IEEE MIC的方法,这就像我们的方法,他们获得了良好的效果。它们的方法和我们的主要差异是(1)数据采集的能量范围,(2)窄能量窗口的宽度,以及(3)计算初级光子数量的方法。本文调查了他们的方法和我们的方法,同时考虑到上述三点。使用Monte Carlo仿真数据和实验数据进行评估性能。在模拟中,我们使用了MCAT幻像和精度通过重建图像中的平均平方误差来评估。结果表明,我们的方法的准确性略微优于El Fakhri的方法。在实验中,我们将能量范围固定为120-180 kev,并将窄能量窗口的宽度变为2.2,4.4和6.7 keV。结果表明,2.2 keV的窗宽对于能量窗口太窄而来。总之,证实我们的方法略微优于El Fakhri的方法,并且两种方法在分离/ SOP 99m / TC和/ SUP 123 / S两种方法方面都是相当有效的。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号