ITR/IM: Novel Indexing and Retrieval of Dynamic Brain Images

paul KantorRutgers university动态脑图像的新颖建模索引和检索提议的研究将开发动态脑图像的表示，组织和检索新技术。两个地点的高分辨率脑成像设备将进行有针对性的实验，以开发支持研究的图像序列。多种技术将被用于提供比原生fMRI格式更高的时间分辨率。图片将被存档，供研究团队和世界其他地方的其他团队访问。这项研究将开发新的大脑活动模型和有效的索引和检索这些事件的方案。该项目的一个实际研究目标是支持一种新的“按例查询”访问时空脑图像档案，供临床医生和研究人员用于研究和诊断。该项目还有助于认知科学的临床应用、科学知识的进步以及本科、研究生和研究生水平的科学教育。罗格斯-普林斯顿项目是认知科学家、计算机科学家和工程师、信息科学家、应用数学家、统计学家和认知神经科学家的合作项目，由临床医生和放射科医生组成的咨询委员会提供指导。开发的算法将更好地近似训练有素的人类在扫描存储图像阵列以寻找与给定图像“相似”的图像时所做的判断，即“按示例查询”。该项目将有助于为临床和工业研究人员提供神经成像分析工具，这些研究人员最适合将新方法应用于应用领域。

EIA-0205178Paul KantorRutgers UniversityNovel Modeling of Dynamic Brain Images for Indexing and RetrievalThe proposed research will develop new techniques for representation, organization and retrieval of dynamic brain images. High resolution brain imaging facilities at two sites will conduct targeted experiments to develop image sequences supporting the research. Multiple techniques will be used to provide higher time resolution than the native fMRI format. Images will be archived with web access for the research team, and for other teams elsewhere around the world. The research will develop novel models of episodes of brain activity and effective schemes for indexing and retrieving those episodes. A practical research goal of the project is to support a new kind of "Query by Example" access to archives of space-time brain images, usable by clinicians and researchers for research and diagnosis. The project also contributes to clinical applications of cognitive science, to the advance of scientific knowledge, and to scientific education, at the undergraduate, graduate and post-graduate levels. The Rutgers-Princeton project is a collaboration among cognitive scientists, computer scientists and engineers, information scientists, applied mathematicians, statisticians, and cognitive neuroscientists, with guidance from an advisory committee of clinicians and radiologists.The algorithms developed will better approximate judgments that trained humans make when scanning an array of stored images for ones "similar to" a given image, that is, "Query by Example". This project will help to make neuro-imaging analysis tools available to the clinical and industrial investigators who are best positioned to adapt new methods to applied domains.