RECONSTRUCTION ALGORITHM FOR MULTI-SLICE SPIRAL X-RAY CT

多排螺旋X射线CT重建算法

• 批准号: 6615735
• 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
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-08-01 至 2005-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6615735
• 关键词: Internet; X ray; bioimaging /biomedical imaging; computed axial tomography; computer program /software; computer system design /evaluation; information dissemination

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.

项目描述（申请人提供）：本项目涉及利用螺旋数据采集的多层螺旋CT重建算法的开发。随着最近多排探测器的引入以及在不到500毫秒的时间内获取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。与单排CT扫描仪相比，配备多排检测器的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行扫描仪上得到证实，并且随着检测器行数的增加，这些优势将变得越来越显著。最终，一个强大的成像系统，能够实现早期和可靠的诊断许多疾病将可用于生物医学研究。在4排以上的情况下，梁的锥束散度在重建过程中不可忽略。然而，从数学的角度来看，设计一个能准确解释这种差异的算法是一个挑战。螺旋CB重建算法的设计并不是CT制造商优先考虑的问题，因为许多技术问题阻碍了多排探测器扫描仪的发展。然而，多层螺旋CT的未来取决于该领域的进展。为了充分发挥多行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。