MRI: Acquisition of a Desktop, High-Resolution, Three-Dimensional X-Ray Computed Tomography (CT) System

MRI：购买台式高分辨率三维 X 射线计算机断层扫描 (CT) 系统

• 批准号: 0421000
• 负责人: Shreekanth Mandayam
• 金额: $ 23.87万
• 依托单位: Rowan University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-01 至 2006-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0421000&HistoricalAwards=false
• 关键词: MRI; Acquisition; Desktop; Resolution; Three

This proposal seeks support to acquire the SkyScan 1072 compact, desk-top X-Ray microtomograph system for the non-destructive, high spatial resolution (1.8mm/pixel), three-dimensional reconstruction of objects. Research applications include particle characterization (sand, toner, etc.) and imaging of stress-corrosion cracks in gas pipelines.The proposed acquisition enhances the existing imaging capabilities in the nondestructive evaluation laboratory (NDE Lab) at Rowan University. Presently, we are able to image test objects using the following sensor modalities - magnetic, ultrasonic, thermal, acoustic, optical and 2-D X-Ray. We are developing digital image processing and artificial intelligence (AI) algorithms for predicting 3-D object profiles. These profiles are then visualized using the Virtual Reality (VR) system. However, currently, we do not have the capability to validate the accuracy of the sensor methods and the AI algorithms in predicting these 3-D profiles. The proposed X-Ray computed tomography (CT) system will provide us with exactly that capability; and serve as a validation "gold" standard.Intellectual merit of the proposed activityThe acquisition and use of a CT system that provides 3-D reconstruction of object shapes as a validation "gold" standard significantly benefits the design of artificial neural network algorithms that are employed to predict 3-D shapes from conventional and emergent 2-D imaging techniques. This procedure allows us to develop novel NDE imaging methods that can explicitly demonstrate the various trade-offs that are involved in accurate 3-D characterization of object shapes.Broader impacts of the proposed activityThe NDE Lab in the Rowan University College of Engineering is a multi-disciplinary, collaborative research and teaching laboratory that supports the R&D efforts faculty, students (both graduate and undergraduate) and industrial partners. The proposed acquisition will positively impact research activities among other faculty not only in the College of Engineering, but also across Campus. Collaborations that are underway include the development of smart-sensors and bio-sensors -the reliability of these deviceswill be tested using the proposed CT scanner.Previously funded research projects in the NDE Lab have demonstrated significant educational impact. To date, the Lab has employed 32 undergraduate research assistants and 10 graduate research assistants. The Lab has supported an average of three multidisciplinary Engineering Clinic projects every semester since Fall 1999, impacting approximately 120 students. So far, 9 Faculty from three engineering disciplines (ECE, ME, CEE) have collaborated on research and education projects. We anticipate that 10 undergraduate students and 2 graduate students will use the proposed instrument every semester.

这项提议寻求支持，以获得SkyScan 1072紧凑型台式X射线显微断层摄影系统，以便对物体进行无损、高空间分辨率(1.8 mm/像素)的三维重建。研究应用包括颗粒表征(沙子、碳粉等)以及天然气管道应力腐蚀裂纹的成像。拟议的收购增强了罗文大学无损评估实验室(NDE Lab)的现有成像能力。目前，我们能够使用以下传感器模式对测试对象进行成像--磁、超声、热、声、光和二维X射线。我们正在开发用于预测三维物体轮廓的数字图像处理和人工智能(AI)算法。然后使用虚拟现实(VR)系统将这些配置文件可视化。然而，目前我们还没有能力验证传感器方法和人工智能算法在预测这些三维轮廓方面的准确性。拟议的X射线计算机断层扫描(CT)系统将为我们提供这种能力；并作为验证的“金”标准。建议活动的智力优点获得并使用提供物体形状三维重建的CT系统作为验证的“金”标准，大大有助于人工神经网络算法的设计，该算法用于从传统的和新兴的二维成像技术预测三维形状。这个程序允许我们开发新的无损检测成像方法，可以清楚地展示物体形状的准确3D表征所涉及的各种权衡。拟议活动的广泛影响罗文大学工程学院的无损检测实验室是一个多学科、协作的研究和教学实验室，支持研发工作的教师、学生(研究生和本科生)和行业合作伙伴。拟议中的收购不仅将对工程学院其他教职员工的研究活动产生积极影响，还将对整个校园的研究活动产生积极影响。正在进行的合作包括开发智能传感器和生物传感器--这些设备的可靠性将使用拟议的CT扫描仪进行测试。先前在无损检测实验室资助的研究项目已经证明了重大的教育影响。到目前为止，该实验室已聘请了32名本科生研究助理和10名研究生研究助理。自1999年秋季以来，该实验室平均每学期支持三个多学科工程诊所项目，影响到大约120名学生。到目前为止，来自三个工程学科(欧洲经委会、ME、CEE)的9个学院在研究和教育项目上进行了合作。我们预计每学期将有10名本科生和2名研究生使用该仪器。