CORE--IMAGE ANALYSIS

在这个项目中，将产生大量的图像数据，由多个调查人员共享。这些图像数据包括多个探头的MRI和PET，其中一些在不同的时间点重复，需要有序地组织、可靠地归档，并便于调查人员访问。此外，图像处理和分析程序需要在不同的项目之间可靠和一致地执行。因此，这个核心的目标是提供图像处理和分析资源，以支持本计划项目赠款的三个项目的调查人员，以促进他们的科学调查。图像分析核心有三个具体目标。 目的1.有序地组织图像数据，以方便调查人员访问，并控制图像质量和图像的完整性。 目的2.简化和统一图像处理，并从图像中提取与生物相关的信息。 目的3.整合提取的信息并进行统计分析和评价。 将建立和维护一个基于因特网的图像数据库系统，以满足目标1的要求。目标2和3包括许多图像和数据分析业务。每个受试者的多个模式的图像将被共同配准，参数图像(具有直接的生物/功能意义)将从PET研究中产生。之后，将进行两个主要分析。一种是将不同受试者的图像与一个共同的参考集对齐，从这个参考集开始，ROI分析和基于像素的分析都将在整个大脑的3D体积上执行。第二个主要分析是将不同受试者的大脑半球皮质表面映射到一个参考集。根据导出的映射图，可以确定大脑皮层表面的皮质测量，包括灰质厚度和PET衍生的功能活动。 将与三个研究项目的调查人员密切互动，进行统计分析。对于动物研究的图像数据，将建立一个单独的图像数据库，类似于人体受试者的图像数据库。图像联合配准和生成生物/功能图像的过程将与人体研究的过程平行。

A large volume of image data, to be shared by multiple investigators, will be generated in this program project. These image data, which include MRI and PET of multiple probes and some of which are repeated at different time points, need to be orderly organized, reliably archived, and conveniently accessible by investigators. Furthermore, image processing and analysis procedures need to be performed reliably and consistently among different projects. The goal of this core is thus to provide image handling and analysis resources to support the investigators of the three projects of this Program Project Grant to facilitate their scientific investigations. The Image Analysis Core has three specific aims. Aim 1. To organize image data orderly to allow convenient investigator access and to control image quality and integrity of images. Aim 2. To streamline and to unify image processing, and to extract biologically relevant information from images. Aim 3. To integrate the extracted information and to perform statistical analysis and evaluation. An Internet-based image database system will be set up and maintained to address Aim 1. Aims 2 and 3 encompass many image and data analysis operations. Images of multiple modalities for each subject will be co-registered, and parametric images (with direct biological/functional meaning) will be generated from PET studies. Afterward, two rriajor analyses will be performed. One is to align images of different subjects to a common reference set, from which both ROI analysis and pixel-based analysis will be performed over the entire 3D volume of the brain. The second major analysis is to map the brain hemispheric cortical surface of different subjects to a reference set. From the derived mapping, cortical measures that include gray matter thickness and PET-derived functional activities can be determined for the brain cortical surface. Statistical analyses will be performed in close interaction with investigators of the three research projects. For image data of animal studies, a separate image database, similar to the one for images of human subjects, will be set up. The procedures of image co-registration and the generation of biological/functional images will parallel those for human studies.