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Equipment: MRI: Track 2 Acquisition of a Novel Performance-Driven 3D Imaging System for Extremely Noisy Objects (NPIX)

Equipment: MRI: Track 2 Acquisition of a Novel Performance-Driven 3D Imaging System for Extremely Noisy Objects (NPIX)
设备: MRI:第 2 道采购新型性能驱动的 3D 成像系统,用于极噪物体 (NPIX)
批准号:
2319708
负责人:
Navid Asadi
金额:
$260.0万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-10-01 至 2026-09-30

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中文摘要
翻译
X光机在医学、工程、农业和牙科等各个领域都有广泛的应用。它们被用来捕捉牙齿、骨骼和半导体芯片等小部件的高质量图像,以便进行详细分析。然而,目前的X光机在处理复杂形状的部件时,往往会产生噪声严重且分辨率较低的图像。因此,理解这些问题并确定潜在的解决方案变得极其具有挑战性。该项目的目标是获得一种先进的系统,以解决这些限制。新型性能驱动的极噪声物体3D成像系统(NPIX)将具有增强的能力,以最小的噪声捕捉复杂几何形状的物体的图像。NPIX系统提供了许多超越传统层析成像和层析成像的先进功能。NPIX大大减少了在不同研究领域进行自动图像分析所需的训练数据集大小,仅为数十或数百个图像,而不是数百万个。由此产生的低噪声图像增强了最先进的人工智能和深度学习算法,将传统的X射线成像提升到了新的高度。因此,这个系统成为各种研究和工业应用的宝贵工具。NPIX系统的设计是用户友好和可访问的,是教育和培训目的的理想选择。该项目旨在以多种方式利用该系统:1)向全国在校和校外学生提供机会;2)通过学生科学培训计划(SSTP)将X射线专业知识整合到K-12教育中;3)与本科生研究教育(REU)和服务奖学金(SFS)计划合作,让本科生接触X射线技术;4)为实践培训提供继续教育选择;5)让本科生和代表性不足的学生参与研究;6)与少数族裔服务机构合作;7)向来自当地学校、社区学院和大学的参观者展示该系统,以激励未来的领导人。该项目将涉及从不同领域的NPIX系统收集大量X射线图像。这些资源可以在https://paine-conference.org/resources/.上访问这些共享的资源可以让社区参与到不同的领域,并帮助自动化和增强检查和保证过程。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
X-ray machines have found extensive applications in various fields, including medicine, engineering, agriculture, and dentistry. They are utilized to capture high-quality images of small components such as teeth, bones, and semiconductor chips for detailed analysis. However, the current X-ray machines often produce images with significant noise and poor resolution when dealing with intricately shaped parts. Consequently, comprehending the issues and identifying potential solutions becomes exceedingly challenging. The objective of this project is to acquire an advanced system that addresses these limitations. The Novel Performance-Driven 3D Imaging System for Extremely Noisy Objects (NPIX) system will possess enhanced capabilities to capture images of the objects with complex geometries with minimal noise. The NPIX system offers numerous advanced capabilities surpassing conventional tomography and laminography. NPIX significantly reduces the required training dataset size to merely tens or hundreds of images, as opposed to millions, for automated image analysis in various research areas. The resulting low noise images enhance state-of-the-art AI and deep learning algorithms, elevating conventional X-ray imaging to new heights. As a result, this system becomes a valuable tool for a diverse array of research and industrial applications.The NPIX system is designed to be user-friendly and accessible, ideal for educational and training purposes. The project aims to utilize the system in multiple ways: 1) offering access to both on campus and off campus students nationally; 2) integrating X-ray expertise into K-12 education through the student science training program (SSTP); 3) partnering with research education for undergraduates (REU) and scholarship for service (SFS) programs, Neocity academy to expose undergraduate students to X-ray techniques; 4) providing continued education options for practical training; 5) involving undergraduate and underrepresented students in research; 6) collaborating with minority-serving institutions; 7) showcasing the system to visitors from local schools, community colleges and universities to inspire future leaders.The project will involve collecting a large amount of X-ray images from the NPIX system in different fields. These resources can be accessed at https://paine-conference.org/resources/. These shared resources can engage the community in different areas and help automating and enhancing inspection and assurance processes.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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