Center for Grid-Enabled Medical Image Analysis

描述（由申请人提供）：随着医学研究和临床实践对从各种成像模式获得的复杂数据集的日益重视，迫切需要图像处理、分析和存储能力的进步。与图像相关联的分辨率在尺度上从宏观（例如，放射学研究）到显微镜（来自活组织检查的载玻片）。图像可以是二维或三维的，静态的或时间依赖的，并且数据产生丰富的代谢和解剖信息。虽然能够获得这些丰富的信息有可能彻底改变我们对疾病病理生理学的理解以及对患者疾病的非侵入性诊断，但处理、分析和存储大量图像数据的需求提出了巨大的挑战。在从基础研究到临床研究的各个领域，如果不利用强大的分布式计算资源来处理多个站点的海量数据和数据集的处理要求，就无法实现成像技术的巨大前景。这些地点可能位于医疗中心和大学内，也可能跨越许多地理上分散的机构。 虽然OSU和OSC研究人员和提案中描述的资源构成了中心的理想基础，但需要一个预NPEBC来利用现有的OSU资源来促进高度协作的研究和培训环境的发展。如果没有一个中心，我们只能看到一组稀疏的非交互式成像相关合作。该中心的环境将产生高度创新的跨学科项目，并将为新的科学家提供无与伦比的培训机会。此外，这将使俄勒冈州立大学能够培养跨学科的科学家，精通成像方法，计算以及在临床和研究环境中的使用。

DESCRIPTION (provided by applicant): With the increasing emphasis of medical research and clinical practice on complex datasets obtained from a variety of imaging modalities, there is a great need for advances in image processing, analysis, and storage capabilities. The resolution associated with the imagery varies in scale from macroscopic (e.g., radiology studies) to microscopic (slides from biopsies). The imagery can be two or three-dimensional, static or time dependent, and the data yield a wealth of metabolic and anatomic information. While having the ability to obtain this wealth of information has the potential to revolutionize our understanding of disease pathophysiology as well as the noninvasive diagnosis of disease in patients, the need to process, analyze and store this large amount of image data presents a great challenge. In areas ranging from fundamental basic to clinical research, the great promise of imaging technology cannot be realized without exploiting powerful distributed computing resources to handle the massive data and processing requirements of datasets at multiple sites. The sites may lie within a medical center and University or may span many geographically separated institutions. While the OSU and OSC researchers and the resources described in the proposal form an ideal substrate for a center, a pre-NPEBC is needed to leverage existing OSU resources to catalyze development of a highly collaborative research and training environment. Without a center, we would expect only to see a sparse set of non-interacting imaging-related collaborations. The Center environment would produce highly innovative interdisciplinary projects and would provide new scientists with unparalleled training opportunities. Furthermore, this would enable OSU to train inter-disciplinary scientists, well-versed in imaging methods, computing and the use of both in the clinical and research environment.