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RECONSTRUCTION ALGORITHM FOR MULTI-SLICE SPIRAL X-RAY CT

多排螺旋X射线CT重建算法

基本信息

批准号：
6779809
负责人：
Frederic Noo
金额：
$ 14.95万
依托单位：
UNIVERSITY OF UTAH
依托单位国家：
美国
项目类别：
财政年份：
2002
资助国家：
美国
起止时间：
2002-08-01 至 2006-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/6779809
关键词：
Internet X ray bioimaging /biomedical imaging computed axial tomography computer program /software computer system design /evaluation information dissemination

项目摘要

DESCRIPTION (provided by applicant): This project involves the development of reconstruction algorithms for multislice CT using helical data acquisition. With the recent introduction of multi-row detectors and the ability to acquire data over 360 degrees in less than 500 ms, x-ray CT is undergoing a new phase of rapid innovation. Compared to single-slice CT scanners, CT scanners with multi-row detectors can cover larger volumes, achieve higher axial resolution, avoid motion artifacts due to respiration, and improve the detectability of low-contrast details. These advantages have been identified with 4-row scanners and will become increasingly significant with greater numbers of detector rows. Eventually, a powerful imaging system with the capability of achieving early and reliable diagnosis of numerous diseases will be available for biomedical research. With more than 4 rows it is known that the cone-beam (CB) divergence of the beams cannot be neglected during reconstruction. However, from a mathematical point-of-view, designing an algorithm that accurately accounts for this divergence poses a challenge. The design of helical CB reconstruction algorithms is not a priority for CT manufacturers due to the numerous technological problems hindering the development of scanners with multi-row detectors. However, the future of multi-slice CT depends on progress that can be made in this field. Highly accurate reconstruction algorithms are needed to realize the full potential and development of multi-row scanners. This research project aims to satisfy that need. The specific aims are (1) to implement, characterize, and compare existing helical CB reconstruction algorithms, using a collection of figures-of-merit, and to disseminate the coded algorithms; (2) to derive, implement, and characterize new helical CB reconstruction algorithms that provide 3D images with isotropic spatial resolution and high local temporal resolution (< 300 ms); and (3) to derive, implement and characterize new helical CB reconstruction algorithms that provide 3D images with isotropic spatial resolution and high detectability of low-contrast details (possibly at the expense of temporal resolution). Indirectly, this project will have significant impacts on all aspects of medical imaging - particularly in oncology, angiography, evaluation of infections and cardiac diseases, trauma, and radiotherapy.

描述(由申请人提供)：该项目涉及使用螺旋数据采集的多层CT重建算法的开发。随着最近多行探测器的引入以及在不到500毫秒的时间内获得360度以上数据的能力，X射线CT正在经历一个快速创新的新阶段。与单层CT扫描仪相比，多排探测器的CT扫描仪可以覆盖更大的体积，实现更高的轴向分辨率，避免因呼吸引起的运动伪影，并提高低对比度细节的可检测性。这些优势已经在4行扫描仪中得到确认，并且随着探测器行数量的增加，这些优势将变得越来越显著。最终，一种强大的成像系统将可用于生物医学研究，该系统能够实现对多种疾病的早期和可靠诊断。在4列以上的情况下，光束的锥束发散在重建过程中是不能忽略的。然而，从数学的角度来看，设计一种准确地解释这种差异的算法是一个挑战。螺旋CB重建算法的设计不是CT制造商的优先事项，因为许多技术问题阻碍了具有多行探测器的扫描仪的发展。然而，多层螺旋CT的未来取决于该领域能否取得进展。为了充分发挥多排扫描仪的潜力和发展，需要高精度的重建算法。本研究项目旨在满足这一需求。具体目标是(1)使用一组品质因数来实现、表征和比较现有的螺旋CB重建算法，并传播编码算法；(2)推导、实现和表征提供具有各向同性空间分辨率和高局部时间分辨率(300ms)的3D图像的新的螺旋CB重建算法；以及(3)推导、实现和表征提供具有各向同性空间分辨率和低对比度细节的高可检测性(可能以时间分辨率为代价)的3D图像的新的螺旋CB重建算法。间接地，该项目将对医学成像的所有方面产生重大影响，特别是在肿瘤学、血管造影术、感染和心脏疾病的评估、创伤和放射治疗方面。