Hardware for Ultra-Fast CT Reconstruction

用于超快速 CT 重建的硬件

• 批准号: 7638537
• 负责人: Jeffrey Brokish
• 金额: $ 36.1万
• 依托单位: INSTARECON, INC.
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-08-01 至 2011-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7638537
• 关键词: Acceleration; Achievement; Algorithms; Architecture; Arts; Benchmarking; Calculi; Cardiac; Clinical; Clinical Data; Code; Complex; Computer Systems; Computer software; Computers; Conflict (Psychology); Coupled; Coupling; Data; Data Set; Development; Diagnostic; Diagnostic Imaging; Dose; Drug Formulations; Elements; Ensure; Equilibrium; Evaluation; Family; Fluoroscopy; Foundations; Future; Generations; Goals; Hand; Healthcare; Illinois; Image; Industry; Lead; Legal patent; Licensing; Life; Literature; Logic; Manufacturer Name; Maps; Mathematics; Measures; Medical; Metals; Methodology; Methods; Morphologic artifacts; Operative Surgical Procedures; Output; Phase; Price; Problem Solving; Process; Relative (related person); Research; Research Design; Research Personnel; Resources; Retinal Cone; Rotation; Scanning; Scientist; Security; Slice; Solid; Solutions; Source; Speed; System; Technology; Testing; Thick; Three-Dimensional Image; Time; Translating; Trauma; Universities; Update; Validation; Variant; Work; base; clinically relevant; commercialization; computerized data processing; cost; data acquisition; design; detector; flexibility; image reconstruction; imaging modality; improved; interest; mathematical algorithm; millimeter; next generation; novel; novel diagnostics; prototype; radiologist; reconstruction; research study; success; tomography; whole body imaging

DESCRIPTION (provided by applicant): Image reconstruction in x-ray computer tomography (CT) scanners lags far behind the data acquisition. For example a whole-body scan using the latest 64-slice medical CT scanners, with sub-millimeter slice thickness, which takes about 10 seconds to acquire, requires about 20 times as long to reconstruct. This computational lag occurs despite the use of expensive special-purpose computing hardware. Faster image reconstruction is critical for life-threatening trauma cases, and is key to enhancing the use of x-ray CT as a dynamic real-time imaging modality for cardiac imaging, fluoroscopy and interventional applications. Furthermore, faster reconstruction is needed to enable new applications using computationally demanding iterative reconstruction methods that can overcome metal artifacts, improve image quality, and reduce the x-ray dose required to achieve acceptable image quality. Similarly, faster reconstruction is desired in CT security imaging, especially for scanning of checked luggage at airports. To date, acceleration of image reconstruction in CT scanners has been achieved only by scaling the computing hardware. However, because of the ever-increasing speed demands, simply scaling the hardware (parallelizing, upsizing, or using more processors) carries a prohibitive price tag. The objective of this project is to achieve very large speed-ups through the use of more clever image reconstruction algorithms (i.e. more clever mathematics), which were developed and patented at the University of Illinois and have been licensed to InstaRecon. These algorithms reduce the mathematical operation counts for the reconstruction by factors of 10 to 50 for 512 W 512 pixel images typical in medical applications. We propose to develop, evaluate, and validate a hardware prototype of an ultra-fast algorithmically-accelerated image reconstruction engine for three- dimensional cone-beam CT scanners. The hardware platform will be a reconfigurable field-programmable object array (FPOA), which offers an attractive tradeoff between cost, speed, and flexibility. Specific aims of this project are prototypes of (i) an ultra-fast algorithmically accelerated hardware backprojector for the 3D circular imaging scan geometry; (ii) a fast complete software reconstruction algorithm for the 3D helical cone beam geometry, for the so-called long object problem, applicable to diagnostic imaging; and (iii) an ultra-fast algorithmically accelerated complete hardware reconstructor for the 3D helical cone beam long object geometry. We aim to provide a speed-up of at least 20W relative to two benchmarks: (i) conventional algorithms implemented on comparable hardware resources, and (ii) current best-in class commercial CT reconstruction rates. These speed-ups can be used to implement more sophisticated algorithms to produce better image quality and for low-dose imaging. Stringent control of image quality by both objective and subjective measures and experiments will be applied throughout the course of the project to ensure that the unprecedented speed-up is achieved while maintaining pristine image quality.

描述（由申请人提供）：X射线计算机断层扫描（CT）扫描仪中的图像重建远远落后于数据采集。例如，使用最新的64层医学CT扫描仪进行全身扫描，其切片厚度为亚毫米，采集时间约为10秒，重建时间约为20倍。尽管使用昂贵的专用计算硬件，这种计算滞后还是会发生。更快的图像重建对于危及生命的创伤病例至关重要，并且是增强X射线CT作为心脏成像、荧光透视和介入应用的动态实时成像模式的使用的关键。此外，需要更快的重建，以使新的应用程序使用计算要求的迭代重建方法，可以克服金属伪影，提高图像质量，并减少所需的X射线剂量，以达到可接受的图像质量。类似地，在CT安全成像中期望更快的重建，特别是对于在机场的托运行李的扫描。迄今为止，在CT扫描仪中的图像重建的加速已经仅通过缩放计算硬件来实现。然而，由于速度需求不断增加，简单地扩展硬件（并行化、大型化或使用更多处理器）会带来令人望而却步的价格标签。该项目的目标是通过使用更聪明的图像重建算法（即更聪明的数学）来实现非常大的速度提升，这些算法由伊利诺伊大学开发并获得专利，并已授权给InstaRecon。这些算法减少了数学运算计数的重建的因素为10至50的512 W 512像素的图像在医疗应用中的典型。我们建议开发、评估和验证用于三维锥束CT扫描仪的超快速算法加速图像重建引擎的硬件原型。硬件平台将是一个可重构的现场可编程对象阵列（FPOA），它提供了一个有吸引力的成本，速度和灵活性之间的权衡。该项目的具体目标是：（一）用于三维圆形成像扫描几何结构的超快速算法加速硬件反投影仪的原型;（二）用于三维螺旋锥束几何结构的快速完整软件重建算法，用于所谓的长物体问题，适用于诊断成像;以及（iii）用于3D螺旋锥形束长对象几何形状的超快速算法加速的完整硬件重建器。我们的目标是提供至少20 W的速度提升相对于两个基准：（i）传统算法上可比的硬件资源，（ii）目前最好的同类商业CT重建率。这些加速可用于实现更复杂的算法，以产生更好的图像质量和低剂量成像。在整个项目过程中，将通过客观和主观的测量和实验对图像质量进行严格控制，以确保在保持原始图像质量的同时实现前所未有的速度提升。