Center for Grid-Enabled Medical Image Analysis

描述(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，对图像处理、分析和存储能力的进步有很大的需求。与图像相关的分辨率在尺度上从宏观(例如放射学研究)到微观(活组织切片)各不相同。图像可以是二维或三维的，静态的或依赖于时间的，数据产生了丰富的新陈代谢和解剖信息。虽然拥有获得这些丰富信息的能力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、分析和存储如此大量的图像数据的需求是一个巨大的挑战。在从基础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需求，成像技术的巨大前景就无法实现。这些地点可能位于一个医疗中心和大学内，也可能跨越许多地理上分离的机构。 虽然俄勒冈州州立大学和俄勒冈州州立大学的研究人员以及提案中描述的资源构成了一个中心的理想基础，但需要一个预先的NPEBC来利用现有的俄勒冈州州立大学的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，我们预计只会看到一组与成像相关的非交互协作。该中心的环境将产生高度创新的跨学科项目，并将为新科学家提供无与伦比的培训机会。此外，这将使俄亥俄州立大学能够培训跨学科的科学家，他们精通成像方法、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.