STRUCTURAL ANALYSIS OF ANATOMICAL SHAPES AND OF WHITE MATTER TRACTS

脑结构的体内成像研究提供了关于脑损伤性质的有价值的信息。 神经精神病症，包括神经变性疾病和/或异常神经系统疾病， 神经发育影像学可以描述功能和形态学信息，已成为检测正常生物变异性和正常变化的重要组成部分。图像 在空间分辨率、对比噪声比、高速成像和测量组织和功能的各种性质的扫描序列的多功能性方面，采集显示出稳定的进展。为了跟上成像技术的发展和临床研究的需要，图像分析研究必须开发适合于探索性研究和大型临床研究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，如果开发一个健全的数学基础和生产通用工具集成到一个共同的平台上的原则，将不仅适用于人类神经成像研究，如这里提出的，但将是相关的癌症研究中的成像研究，各种其他成像领域，如动物成像研究，甚至共聚焦显微镜成像，例如。

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.