NEUROMORPHOMETRY IN SCHIZOPHRENIA BY COMPUTER ALGORITHM, ALZ BY BRAIN MAPPING

这个子项目是利用由NIH/NCRR资助的中心拨款提供的资源的许多研究子项目之一。子项目和调查员(PI)可能从另一个NIH来源获得了主要资金，因此可能会出现在其他CRISE条目中。列出的机构是针对中心的，而不一定是针对调查员的机构。资源赠款促进了由John G.Csernansky医学博士指导的两项赠款。这两项赠款都依赖于将在TRD4中开发的皮质分析方法，以补充深灰质大脑结构和人脑皮质表面的高维映射。这些资助涉及阐明神经精神障碍患者，特别是精神分裂症和阿尔茨海默型痴呆症患者海马区的大脑结构异常。在这两种情况下，这类人可能存在的海马体结构异常都是微妙的，使用手动估计大脑结构体积的传统方法很难检测到。目前用于估计脑结构体积的计算解剖学方法(Haller等人，1997)和使用海马体结构形状的度量进行组比较的方法已经被开发出来。在区分神经精神疾病患者和对照组方面，这些指标似乎优于大体积法(Csernansky等人，1998,2000)。如下文所述，在TRD4中开发的方法将对分析扣带回等大脑结构的神经形态计量学变化非常重要。例如，在TRD4的目标3中开发的沟匹配和生成算法将用于分析由TRD4的目标1中开发的算法生成的扣带回皮质表面的沟特征的细微变化。进展：已对10个扣带回进行了手工和自动的分割和标注。实验验证了贝叶斯分割的有效性。人们正在检查表面重建相对于手工绘制轮廓的准确性。

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.