NEUROMORPHOMETRY IN SCHIZOPHRENIA BY COMPUTER ALGORITHM, ALZ BY BRAIN MAPPING

该子项目是利用NIH/NCRR资助的中心赠款提供的资源的许多研究子项目之一。子项目和研究者（PI）可能从另一个NIH来源获得了主要资金，因此可以在其他CRISP条目中表示。所列机构为中心机构，不一定是研究者机构。资源补助金促进了由约翰G。Csernansky，医学博士这些赠款都依赖于TRD 4中开发的皮层分析方法，以补充人脑深层灰质脑结构和皮层表面的高维映射。这些赠款涉及阐明神经精神障碍患者海马体的大脑结构异常，特别是精神分裂症和阿尔茨海默型痴呆症。在这两种情况下，可能存在于这些人中的海马结构异常是微妙的，并且难以使用用于手动估计脑结构体积的常规方法来检测。目前已经开发了用于估计脑结构体积（Haller等人，1997）和用于使用海马结构形状的度量进行组比较的计算解剖学方法。在区分神经精神疾病患者与健康对照者方面，这些指标似乎上级于总容量测定法（Csernansky et al，1998，2000）。正如下面的关系中所概述的，TRD 4中开发的方法在分析大脑结构（如扣带回）的神经形态学变化方面将是重要的。例如，TRD 4目标3中开发的脑沟匹配和生成算法将用于分析TRD 4目标1中开发的算法生成的扣带回皮质表面脑沟特征的细微变化。研究进展：10个扣带回已经被人工和自动分割和注释。实验验证了贝叶斯分割的有效性。表面重建正在检查其相对于手工轮廓的准确性。

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. The Resource Grant facilitates two grants directed by John G. Csernansky, M.D. These grants both depend upon methods of cortical analysis to be developed in TRD4 to complement high dimensional mappings of deep gray matter brain structures and cortical surfaces of the human brain. These grants involve the elucidation of brain structure abnormalities in the hippocampus of patients with neuropsychiatric disorders, specifically schizophrenia and dementia of the Alzheimer type. In both cases, hippocampal structure abnormalities likely to be present in such persons are subtle and difficult to detect using conventional methods for manual estimations of brain structure volumes. Current computational anatomy methods for estimating brain structure volumes (Haller, et al, 1997) and for group comparisons using metrics of hippocampus structure shape have been developed. These metrics appear to be superior to gross volumetry in discriminating patients with neuropsychiatric disea se from he althy controls (Csernansky et al, 1998, 2000). As outlined below in the relationship, the methods developed in TRD4 will be important in analyzing neuromorphometric changes in brain structures such as the cingulate gyrus. For example, sulcal matching and generation algorithms developed in Aim 3 of TRD4 will be used to analyze subtle changes in sulcal features of cortical surfaces of cingulate gyrus that are generated by the algorithm developed in Aim 1 of TRD4. Progress: 10 Cingulate gyri have been segmented and annotated, both by hand and automatically. Validations have been carried out demonstrated the validatity of Bayes segmentation. Surface reconstructions are being examined for their accuracy relative to hand contouring.