Comprehensive Training program in Imaging Science and Informatics

7.项目摘要/摘要 这项建议的总体主题是培养“综合成像科学家”的技能 确定临床相关问题所必需的；开发仪器、传感器和对比度 代理以形成适合问题的图像；并使用 信号处理、数学建模、可视化和信息学技术，以提高 人类疾病的预防、检测、诊断和治疗。该程序的范围从分子到 从细胞到组织再到器官。为了让成像科学家从图像中了解完整的轨迹 从编队到分析和决策，他们必须在四个核心领域进行培训：仪器、设备、 和造影剂；图像处理；建模和可视化；以及数据挖掘和信息学。 该项目的所有学生都接受了这些领域核心概念的培训。目前的培训计划是 为期两年的博士预科课程。共有41名学生被该项目录取。这个 拟议的续期将再培训20名学生。该项目包括校外实习研究。 经验；深入的临床参与；以及广泛的专业发展组成部分。 影像科学是基础科学研究和临床医学不可或缺的组成部分。成像细胞贩运 和体内受体药理学已经导致了靶向药物和基因治疗，并理解了 细胞生化途径的研究将有助于医学的新进展。个性化医疗依赖于 在很大程度上依靠成像技术来选择最佳治疗方法并监测进展。尽管原地构造 人体成像已经是临床医学的重要组成部分，在功能方面还需要许多进展 对大脑和其他器官进行成像，以改善医疗保健。脑成像是美国国立卫生研究院的核心关注点 研究很大程度上依赖于成像。我们已经确定了成像科学家开发新的 成像仪器，并使用来自图像处理的适当方法应用该仪器； 建模和可视化；以及信息学和数据挖掘。认识到人工智能的潜力 为了改变医学成像的智能化，我们的项目强调了机器学习的应用。 这一培训计划通过提供受过广泛培训的高技能科学家来填补关键的利基市场。 成像科学的发展轨迹。了解仪器和图像分析之间的相互作用， 包括机器学习方法，对于设计下一代硬件和软件非常重要 用于量化复杂生物系统和提供强大的临床工具的工具。这次会议的一个关键成果 该计划的目的是让受训者获得必要的技能，以识别临床相关问题。

7. Project Summary/Abstract The over-arching theme of this proposal is to train “comprehensive imaging scientists” in the skills necessary to identify clinically relevant problems; develop instrumentation, sensors, and contrast agents to form images appropriate for the problem; and analyze the resulting imaging data using signal processing, mathematical modeling, visualization, and informatics techniques to improve the prevention, detection, diagnosis, and treatment of human diseases. The program spans from molecular to cellular to tissue to organ. In order for imaging scientists to be knowledgeable of the full trajectory from image formation to analysis and decision-making, they must be trained in four core areas: Instrumentation, Devices, and Contrast Agents; Image processing; Modeling and Visualization; and Data Mining and Informatics. All students in the program are trained in the core concepts of these areas. The current training program is a two-year pre-doctoral portfolio program. A total of 41 students have been admitted to the program. The proposed renewal will train another 20 students. The program includes off-campus externship research experiences; in-depth clinical engagement; and a wide-ranging professional development component. Imaging Science is an integral element of basic science research and clinical medicine. Imaging cell trafficking and receptor pharmacology in vivo have already led to targeted drug and gene therapies and an understanding of cellular biochemical pathways will contribute to new advances in medicine. Individualized medicine relies heavily on imaging techniques to select the best therapies and monitor progress. Although structural in situ human imaging is already a critical component of clinical medicine, many advances are needed in functional imaging of the brain and other organs to improve healthcare. Brain mapping which is a core focus of NIH research relies heavily on imaging. We have identified a critical need for imaging scientists to develop new imaging instrumentation and apply that instrumentation with appropriate methods from image processing; modeling and visualization; and informatics and data mining. In recognition of the potential of artificial intelligence to transform medical imaging, our program emphasizes applications of machine learning. This training program fills a critical niche by providing highly skilled scientists who are trained in the broad trajectory of imaging science. Understanding the interplay between instrumentation and image analysis, including machine learning methods, is important for designing the next generation of hardware and software tools for quantifying complex biological systems and providing robust clinical tools. A key outcome of the program is that trainees gain the skills necessary to identify clinically relevant problems.