STRUCTURAL ANALYSIS OF ANATOMICAL SHAPES AND OF WHITE MATTER TRACTS

脑结构的活体成像研究提供了关于脑血管疾病本质的有价值的信息 神经精神障碍，包括神经退行性疾病和/或异常障碍 神经发育。影像可以描述功能和形态信息，已成为检测正常生物变异和变化的重要组成部分。图像 采集显示在空间分辨率、对比度噪声比、高速成像以及测量组织和功能的各种属性的扫描序列的多功能性方面稳步进步。为了跟上成像技术的进步和临床研究的需要，图像分析研究必须开发出适合于探索性研究和大型临床研究中假设检验的有效处理工具。先进的图像分析方法和统计分析方法，如果在良好的数学基础上开发，并根据产生集成到公共平台中的通用工具的原则，将不仅适用于这里提出的人类神经成像研究，而且将与癌症研究中的成像研究，以及各种其他成像领域，如动物成像研究，甚至共焦显微镜成像相关。

In-vivo imaging studies of brain structures provide valuable information about the nature of neuropsychiatric disorders, including neurodegenerative diseases and/or disorders of abnormal neurodevelopment. Imaging can depict functional and morphologic information and has become an important component to detect normal biological variability and change from normal. Image acquisition shows steady progress with respect to spatial resolution, contrast-to-noise ratio, highspeed imaging, and versatility of scanning sequences measuring a variety of properties of tissue and function. To keep pace with advances in imaging and with needs of clinical research, image analysis research has to develop effective processing tools suitable for exploratory studies and for testing hypothesis in large clinical studies. Advanced image analysis methodology and statistical analysis methods, if developed on a sound mathematical foundation and on the principle of producing generic tools integrated into a common platform, will not only be applicable to human neuroimaging research as proposed here but will be relevant for imaging studies in cancer research, various other imaging domains like animal imaging studies, and even confocal microscopy imaging, for example.