NORMAL MR NEUROMORPHOMETRY BY GLOBAL PATTERN MATCHING

本子项目是利用由NIH/NCRR资助的中心赠款提供的资源的众多研究子项目之一。子项目和研究者（PI）可能已经从另一个NIH来源获得了主要资金，因此可以在其他CRISP条目中表示。列出的机构是中心的，不一定是研究者的机构。正常大脑中由于生长发育、衰老、两性二态性、侧性和偏手性而产生的微小神经解剖学差异可以通过MRI观察到，但需要精确和准确的方法来检测。现代磁共振脑成像方法提供了关于个体大脑解剖结构的详细体内信息。然而，由于无法快速量化个体间的形态差异，这些解剖数据的解释一直受到阻碍。困难在于两个方面。首先，不同个体之间的图像必须在一个共同的参照系中，但它们不是以这种方式收集的。其次，即使登记，正常的变化也会使比较变得困难，如果不是不可能的话。该建议的主要焦点是发展大脑和特定亚区，特别是海马和颞叶的神经解剖变异的数学表示。这涉及到一个单一的几何图谱映射到多个单独的目标MR图像体积。地图集是一个多值空间阵列，包含信号值（对应于CT、MR和彩色冷冻切片图像）及其符号标签（组织类型、解剖命名法），用于对调查具有医学和生物学意义的所有子卷。这些表示提供了一种独特的工具，用于从图谱（模板）及其子卷到TRD4目标2、3和5中正在开发的目标解剖学家族的平滑图的算法生成。通过这种方式，从正常个体群体中选择的形态特征将被比较。通过评估这些方法在正常人群表征中的表现，我们将能够明确地测试关于异常人群中大脑亚结构变化的假设，这些假设是目前方法无法解决的。进展：与Pat Barta博士合作，我们现在已经实现了上颞区自动分割的算法，允许研究正常的解剖变化，如Vannier资助所规定的。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Small neuroanatomical differences in the normal brain due to growth and development, aging, sexual dimorphism, laterality, and handedness are observable by MRI but require precise and accurate methods for their detection. Modern MR brain imaging methods provide detailed in vivo information regarding the anatomical structure of individual brains. However, interpretation of these anatomic data has been hindered by the inability to expeditiously quantify morphological differences across individuals. The difficulty lies in two areas. First, images between different individuals must be in a common reference frame, but they are not collected in this fashion. Second, even when registered, normal variation makes comparisons difficult if not impossible. The major focus of this proposal is the development of mathematical representations of neuroanatomical variation of the brain and specific subregions, especially in the hippocampus and temporal lobe. This involves mapping of a single m orphometric atlas to multiple individual target MR image volumes. An atlas is a multivalued spatial array that contains signal values (corresponding to CT, MR and color cryosection images) with their symbolic labels (tissue type, anatomic nomenclature) for all subvolumes of medical and biological significance to the investigation. These representations provide a unique tool for the algorithmic generation of smooth maps from an atlas (template) and its subvolumes onto families of target anatomies being developed in aims 2,3 and 5 of TRD4. In this way, selected morphometric features from groups of normal individuals will be compared. By assessing the performance of these methods in the characterization of normal populations, we will be able to definitively test hypotheses regarding brain substructure changes in abnormal populations that cannot be resolved with present methods. Progress: Working with Dr. Pat Barta we have now implemented the algorithms for automated segmentation of superior temporal areas allowing for the study of normal variation of anatomy as specified in the Vannier grant.