Measurement Data Correction for Emission Tomography

摘要：

In the problems of statistical reconstruction of emission tomography images, Bayesian reconstruction, or maximum a posteriori (MAP) method, has proved its superiority over others among all the regularization methods. To further improve the reconstruction, this paper presents a novel statistical image reconstruction method based on coupled feedback (CF) iterative model for emission tomography. This CF iterative algorithm updates the noisy emission sinogram (the measurement data of the detectors) using the latest reconstructed image. The experiments and the performance analysis confirm the virtue of the new method.

关键词： coupled feedback (CF) iterative reconstruction emission tomography Positron emission tomography (PET)

作者: Hao Wu Qingping Zhang

作者单位: Medical Engineering Support Center Chinese PLA (Peoples Liberation Army)General Hospital Beijing,Ch School of Electronic and Information Engineering Shenzhen Polytechnic Shenzhen,China

会议类型: 国际会议

会议名称: The 3rd International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2009)(第三届生物信息与生物医学工程国际会议)

会议地点: 北京

会议语种:英文

页码: 1-4

在线出版日期: 2009-06-11（万方平台首次上网日期，不代表论文的发表时间）