Dept. of Radiol., California Univ., San Francisco, CA.
IEEE Trans Med Imaging. 1994;13(4):627-40. doi: 10.1109/42.363105.
Reports on a new method in which spatially correlated magnetic resonance (MR) or X-ray computed tomography (CT) images are employed as a source of prior information in the Bayesian reconstruction of positron emission tomography (PET) images. This new method incorporates the correlated structural images as anatomic templates which can be used for extracting information about boundaries that separate regions exhibiting different tissue characteristics. In order to avoid the possible introduction of artifacts caused by discrepancies between functional and anatomic boundaries, the authors propose a new method called the "weighted line site" method, in which a prior structural image is employed in a modified updating scheme for the boundary variable used in the iterative Bayesian reconstruction. This modified scheme is based on the joint probability of structural and functional boundaries. As to the structural information provided by CT or MR images, only those which have high joint probability with the corresponding PET data are used; whereas other boundary information that is not supported by the PET image is suppressed. The new method has been validated by computer simulation and phantom studies. The results of these validation studies indicate that this new method offers significant improvements in image quality when compared to other reconstruction algorithms, including the filtered backprojection method and the maximum likelihood approach, as well as the Bayesian method without the use of the prior boundary information.
报告了一种新方法，该方法将空间相关的磁共振（MR）或 X 射线计算机断层扫描（CT）图像用作正电子发射断层扫描（PET）图像贝叶斯重建中先验信息的来源。这种新方法将相关的结构图像作为解剖模板，可用于提取关于分离表现出不同组织特征的区域的边界的信息。为了避免由于功能和解剖边界之间的差异可能导致的伪影的引入，作者提出了一种称为“加权线站点”的新方法，该方法在用于迭代贝叶斯重建的边界变量的修改更新方案中使用先前的结构图像。该修改方案基于结构和功能边界的联合概率。至于 CT 或 MR 图像提供的结构信息，仅使用与相应的 PET 数据具有高联合概率的那些；而其他不受 PET 图像支持的边界信息则被抑制。该新方法已通过计算机模拟和体模研究得到验证。这些验证研究的结果表明，与其他重建算法（包括滤波反投影方法和最大似然方法）以及不使用先验边界信息的贝叶斯方法相比，该新方法在图像质量方面有显著提高。
