NORMAL MR NEUROMORPHOMETRY BY GLOBAL PATTERN MATCHING

正常大脑因生长和发育而产生的微小神经解剖学差异 发育、衰老、性二型性、偏侧性和利手是 通过核磁共振可以观察到，但需要精确和准确的方法才能 侦测。我们建议自动搜索神经形态学 用一种新的数学稳健方法研究脑亚结构的差异 对小的局部和区域形状具有前所未有的敏感性 不同之处。现代磁共振脑成像方法在活体内提供详细的 有关个体大脑解剖结构的信息。 然而，这些解剖数据的解释受到了 无法快速量化 个人。困难在于两个方面。首先，图像之间 不同的个体必须在一个共同的参照系中，但他们不是 以这种方式收集。第二，即使登记在案，也是正常的变异 使比较变得困难，如果不是不可能的话。我们建议进一步 开发用于融合解剖数据的算法工具，通过 全脑核磁共振，所以正常对照人群可以描述为 比较一下。 这项提议的主要焦点是数学的发展 大脑神经解剖变异的表现和特异性 亚区，特别是在海马体和颞叶。这涉及到 将单个形态测量图谱映射到多个单独的目标MR 图像卷。地图集是包含以下内容的多值空间数组 信号值(对应于CT、MR和彩色冰冻切片图像) 它们的符号标签(组织类型、解剖命名法) 对调查具有医学和生物学意义的子卷。 小体积包括特定的脑沟和各种不同的颞叶 (海马区、海马区和颞回)。这些 表示法为算法生成提供了独特的工具 将贴图集(模板)及其子体积平滑映射到 目标解剖。这样，从组中选择的形态测量要素 正常个体的比例将被比较。 通过评估这些方法在表征生物多样性方面的性能 正常人群，我们将能够明确地检验假设 关于异常人群中大脑亚结构的变化 用目前的方法解决了问题。这项工作将提供直接的 用于测量疾病过程的微小影响的形态测量工具。这个 可变形脑图谱将反映潜在的稳定性或 预定义的解剖标记区域，以及与以下各项相关的协变 法线集合中具有生物意义的单个坐标系。我们 将测试该方法识别假想集团间的能力 大脑结构的大小和形状的差异。这一新映射 将显示工具来定位量化个体和群体的大脑 由于正常变异、性别、惯用手和 一边倒。

Small neuroanatomical difference 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. We propose to automate the search for neuromorphological differences in brain substructures by a new mathematically robust method with unprecedented sensitivity to small local and regional shape differences. 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. We propose to further develop algorithmic tools for fusion of anatomical data, as measured via whole brain MRI, so normal control populations can be described and compared. 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 morphometric 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. The subvolumes include specific sulci and various of the temporal lobe (hippocampus, parahippocampal region and temporal gyri). 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. In this way, selected morphometric features from groups of normal individuals will be compared. By assessing the performance of these methods in athe 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. This work will provide a direct morphometric tool for measuring small effects of disease processes. The deformable brain atlas will reflect both the underlying stability or predefined anatomically labeled regions, and t heir covariation relative to a single biologically meaningful coordinate system in sets of normals. We will test the method's ability to identify hypothesized intergroup differences in the size and shape of brain structures. This new mapping tool will be shown to locate the quantify individual and population brain structural differences due to normal variation, gender, handedness, and laterality.