CT Dose Reduction by Fast Iterative Algorithms

通过快速迭代算法减少 CT 剂量

• 批准号: 6994527
• 负责人: Jeffrey Brokish
• 金额: $ 10万
• 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 2007-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6994527
• 关键词: bioimaging /biomedical imaging; computational biology; computed axial tomography; computer program /software; computer system design /evaluation; image processing; mathematical model; radiation dosage; technology /technique development

DESCRIPTION (provided by applicant): Dose reduction for x-ray CT has taken on substantial importance with the increased use of this imaging modality and the imaging of younger patients. The objective of this work is to develop and demonstrate the technical and commercial feasibility of a novel computationally-based approach to the reduction of patient xray dose in diagnostic CT scanners. The approach will use iterative algorithms for the image formation, which can produce high-quality images from low-dose data by incorporating detailed models of the physics and statistics of the data acquisition process. To date, such iterative algorithms have been little used in practice due to their high computational complexity. This problem will be solved by using revolutionary fast algorithms for the backprojection and reprojection steps in the iterative algorithm. The fast approaches to backprojection and reprojection were developed and patented by the University of Illinois. Using this technology, speed-up factors of 10x - 50x have been achieved in software demos. Accordingly, the Phase I aims of this project are to 1) Develop and implement fast statistical and physics-based iterative algorithms for reduced-dose high-precision tomography, and to 2) Evaluate and optimize performance of the fast algorithms in terms of image quality, dose reduction, and computational requirements. In Phase II, the methodology and algorithms will be extended to the dominant imaging geometries: helical multislice, conebeam with a circular source trajectory, and helical conebeam. Significant attention will be devoted to thorough testing of the new dose reduction methods. Commercial adoption of this technology by scanner manufacturers will be encouraged by the potential for increased market share owing to superior low-dose performance; increased sales of CT equipment for dose-critical applications such as pediatric, real-time, and interventional imaging; and affordability. This project promises to revolutionize CT as we know it, by making iterative algorithm-based dose reduction feasible for the first time.

描述（由申请人提供）： 随着X射线CT成像方式的使用和年轻患者的成像越来越多，X射线CT的剂量降低变得非常重要。这项工作的目的是开发和证明一种新的基于计算的方法，以减少诊断CT扫描仪中的患者X射线剂量的技术和商业可行性。该方法将使用迭代算法进行成像，通过结合数据采集过程的物理和统计的详细模型，可以从低剂量数据中生成高质量的图像。迄今为止，这种迭代算法由于其高计算复杂度而很少在实践中使用。这个问题将通过使用革命性的快速算法的反投影和重投影步骤中的迭代算法来解决。反向投影和重新投影的快速方法由伊利诺伊大学开发并获得专利。使用该技术，在软件演示中实现了10倍-50倍的加速系数。因此，该项目的第一阶段目标是：1）开发和实施用于减少剂量高精度断层扫描的快速统计和基于物理的迭代算法，以及2）在图像质量、剂量减少和计算要求方面评估和优化快速算法的性能。在第二阶段，方法和算法将扩展到占主导地位的成像几何形状：螺旋多层，锥束与圆形源轨迹，螺旋锥束。将十分注意彻底测试新的剂量减少方法。由于上级低剂量性能、剂量关键型应用（如儿科、实时和介入成像）的CT设备销量增加以及可负担性，扫描仪制造商对该技术的商业采用将受到市场份额增加潜力的鼓励。该项目有望彻底改变CT，因为我们知道它，使迭代算法为基础的剂量减少第一次可行。