Automated 3D Analysis of Cortical Geometry in MR Images

描述（由申请人提供）：表征人脑结构与其功能之间的关系是当今神经科学中最重要的目标之一。医学成像已被用来获得重要的新的见解，通过使用解剖和生理成像方法的这种关系。尽管最近取得了重大进展，目前的方法仍然是有限的，缺乏自动方法的详细分割，几何分析和标记的大脑皮层。拟议的研究的主要目标是开发全自动化的方法来找到和数学上表示的体积磁共振（MR）图像中的大脑皮层，并自动识别和标记的主要沟回和皮质上使用皮质几何形状的详细统计分析。具体而言，我们建议1）开发和验证方法，以找到和数学上代表大脑皮层的体积磁共振图像; 2）开发和验证方法，计算区域措施的皮质形状和体积; 3）开发和验证自动标记的沟和gryi;和4）进行研究的皮质变异性和体积变化在正常老化。将使用计算机体模和手动体内真实模型对所有方法进行广泛验证。我们开发的用于自动表示和标记大量受试者的皮质的方法也应该在以下方面有用：1）开发正常与患病皮质几何形状的描述，2）用于可变形图谱配准的自动界标生成，3）结构/功能关系的统计相关性研究，以及4）个体发育，发育，衰老和疾病中的形态变化分析。

DESCRIPTION (provided by applicant): Characterizing the relationship between the structure of the human brain and its function is one of the most important goals in neuroscience today. Medical imaging has been used to gain significant new insights into this relationship through the use of both anatomical and physiological imaging methods. Despite significant recent advances, the current methodology is still limited by the lack of automatic methods for the detailed segmentation, geometric analysis, and labeling of the cerebral cortex. The major goals of the proposed research are to develop fully automated methods to find and mathematically represent the cerebral cortex in volumetric magnetic resonance (MR) images and to automatically identify and label the major sulci and gyri on the cortex using a detailed statistical analysis of cortical geometry. Specifically, we propose to 1) develop and validate methods to find and mathematically represent the cerebral cortex from volumetric MR images; 2) develop and validate methods to calculate regional measures of cortical shape and volume; 3) develop and validate automatic labelling of sulci and gryi; and 4) conduct studies of cortical variability and volume changes in normal aging. All methods will be extensively validated using both computer phantoms and manual in vivo truth models. The methods we develop to automatically represent and label the cortex in large numbers of subjects should also be useful in 1) the development of a description of normal versus diseased cortical geometry, 2) automatic landmark generation for deformable atlas registration, 3) statistical correlation studies of structure/function relationships, and 4) the analysis of morphological changes in ontogenesis, phylogenesis, aging, and disease.