Automated brain parcellation and morphometry

磁共振成像(MRI)对活体人脑的非侵入性可视化是临床神经学的重要组成部分。到目前为止，对疾病结构变化的评估主要依赖于定性的视觉判断，或繁琐的手工标记。该项目旨在开发MRI图像处理软件，该软件将自动将整个大脑体积分割成其组成组织和结构。这种分割允许量化组织体积和内在参数。该软件将与我们的结构和功能MRI软件工具套件互操作，例如，允许检查感兴趣的皮质下区域的功能激活。我们建议以脑组织的内在属性为基础进行组织分割，从而使其独立于脉冲序列或扫描仪制造商。这将大大提高扫描/重新扫描的可靠性，这对于多点临床试验或受试者内部的重复测量(例如，比较一段时间内的肿瘤或多发性硬化症斑块)至关重要。拟议的软件将允许核磁共振数据用于检测神经精神疾病，监测此类疾病的病程，并评估治疗的有效性。研究和临床应用有望用于几种神经退行性疾病和精神疾病，如精神分裂症、阿尔茨海默氏症和亨廷顿病。拟议的商业应用：拟议的产品将引起使用磁共振成像的研究人员和临床医生的兴趣，即全球范围内的&gt；10000扫描仪。拟议中的软件可能会成为许多脑部MRI扫描的标准部分，以便检测和量化病理，因此可能会在每年进行的数百万次脑部扫描中使用相当大的比例。最初，该软件将用于在药物评估中执行CNS有效性的替代标记。

Non-invasive visualization of the living human brain with MRI (magnetic resonance imaging) is an essential part of clinical neurology. Until now, evaluation of structural changes in diseases have mainly relied upon qualitative visual judgements, or tedious hand labeling. This project aims to develop MRI image processing software that will automatically segment the entire brain volume into its constituent tissues and structures. This segmentation allows quantification of tissue volumes and intrinsic parameters. The software will be interoperable with our suite of structural and functional MRI software tools, allowing, for example, subcortical regions of interest to be examined for functional activation. We propose to base the tissue segmentation of intrinsic properties of brain tissue, thus rendering it independent of pulse sequence or scanner manufacturer. This will greatly increase scan/rescan reliability which is crucial for multi-site clinical trials, or for within-subject repeated measures (e.g., comparing tumors or multiple sclerosis plaques over time). The proposed software will allow MRI data to be used to detect neuropsychiatric disease monitor the course of such diseases, and evaluate the effectiveness of treatments. Research and clinical applications can be expected in several neurodegenerative and psychiatric diseases such as schizophrenia, Alzheimer's and Huntington's disease. PROPOSED COMMERCIAL APPLICATIONS: The proposed product would be of interest to researchers and clinicians using MRI, i.e., >10000 scanners worldwide. The proposed software could become a standard part of many brain MRI scans, in order to detect and quantify pathology, and thus could potentially be used in a substantial proportion of the millions of brain scans performed every year. Initially, the software would be used to perform surrogate markers of CNS effectiveness in drug evaluation.