Department of Electrical Engineering, KAIST, Korea.
Phys Med Biol. 2011 Aug 7;56(15):4881-94. doi: 10.1088/0031-9155/56/15/015. Epub 2011 Jul 19.
Spatial resolution is intrinsically limited in positron emission tomography (PET) systems, mainly due to the crystal width. To increase the spatial resolution for a given crystal width, mechanical movements such as wobble and dichotomic motions are introduced to the PET systems. However, multiple sinograms obtained through such movements provide oversampled data. In this paper, to increase the spatial resolution, we present a novel super-resolution (SR) scheme that employs multiple sinograms. For SR, we first propose a blur kernel estimation scheme through a Monte Carlo simulation. Based on the estimated blur kernel, we adopt a maximum a posteriori expectation maximization method in estimating a high-resolution sinogram from multiple low-resolution sinograms. The proposed algorithm provides noticeable improvement of the spatial resolution in real PET images.
在正电子发射断层扫描（PET）系统中，空间分辨率本质上受到限制，主要是由于晶体的宽度。为了在给定的晶体宽度下提高空间分辨率，可以向 PET 系统中引入机械运动，如摆动和二分运动。然而，通过这些运动获得的多个正弦图提供了过采样数据。在本文中，为了提高空间分辨率，我们提出了一种利用多个正弦图的新的超分辨率（SR）方案。对于 SR，我们首先通过蒙特卡罗模拟提出了一种模糊核估计方案。基于估计的模糊核，我们采用最大后验期望最大化方法从多个低分辨率正弦图中估计高分辨率正弦图。所提出的算法在真实的 PET 图像中提供了显著的空间分辨率提高。
