Development of a Statistical Medical Image and Data Processing System

本研究计画的目的是在我们先前在统计影像处理的研究成果基础上，发展一个统计医学影像与资料处理系统。为了实现这一目标，我们按照以下三个步骤进行了研究。首先，我们改进了PET和SPECT重建算法和MRI图像分割算法，我们以前开发的计算成本。一般来说，统计图像和数据处理算法需要大量的计算成本，因为它们是基于预定义的成本函数的最小化。然而，改进后的算法工作与合理的计算成本相比，常用的算法。为了实现这一目标，我们引入了块迭代的概念和数学规划领域中的一些优化方法。其次，我们开发了基于统计估计的图像处理算法，以解决医学成像中出现的新问题。例如，这些包括根据一些血管造影X射线投影数据的3-D血管重建、PET和SPECT的分段衰减图重建以及根据医学图像序列的光流计算。为了实现这一目标，我们使用了新的概念，如在数学规划，拓扑约束的图像标记，和小波变换领域的优化方法。最后，将所开发的软件统一在一个工作站上，使它们具有相同的数据格式和使用方法，并将图像显示等用户界面结合在一起。我们评估了这个图像和数据处理系统的性能与几个现有的数据。

The aim of this research project is to develop a statistical medical image and data processing system based on our previous research results on statistical image processing. To achieve this aim, we performed the research according to the following three steps. First, we improved the PET and SPECT reconstruction algorithm and the MRI image segmentation algorithm which we developed previously in terms of computational costs. In general, statistical image and data processing algorithms require a lot of computational costs because they are based on the minimization of pre-defined cost functions. However, the improved algorithms worked with reasonable computational costs comparable to those of the commonly used algorithms. To achieve this aim, we introduced the concept of block iterations and some optimization methods in the field of mathematical programming. Second, we developed image processing algorithms based on statistical estimation for new problems appearing in medical imaging. For example, these include 3-D blood-vessel reconstruction from a few angiographc x-ray projection data, segmented attenuation map reconstruction for PET and SPECT, and optical flow computation from medical image sequences. To achieve this aim we used new concepts such as optimization methods in the field of mathematical programming, topology-constrained image labeling, and wavelet transform. Finally, all the developed softwares are unified in a workstation such that they work with the same data format and the same usage, and some user-interfaces such as image display are combined too. We evaluated the performances of this image and data processing system with several existing data.