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.

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的重建算法的开发。 随着最近引入多行检测器以及在不到500毫秒内获取超过360度的数据的能力，X射线CT正在经历新的快速创新阶段。 与单板CT扫描仪相比，具有多行检测器的CT扫描仪可以覆盖更大的体积，实现更高的轴向分辨率，避免由于呼吸引起的运动伪影并提高低对比度细节的可检测性。这些优势已被4行扫描仪确定，并且随着探测器行的数量，将变得越来越重要。 最终，将有能力实现多种疾病的早期和可靠诊断的强大成像系统，可用于生物医学研究。 在超过4行的情况下，众所周知，在重建过程中不能忽略梁的锥束（CB）差异。 但是，从数学观察点开始，设计一种准确解释这种分歧的算法带来了挑战。 螺旋CB重建算法的设计对于CT制造商而言并不是当务之急，因为许多技术问题阻碍了使用多行探测器的扫描仪的开发。但是，多机CT的未来取决于该领域可以取得的进展。 需要高度准确的重建算法来实现多行扫描仪的全部潜力和发展。 该研究项目旨在满足需求。 具体目的是（1）使用合格图的集合来实施，表征和比较现有的螺旋CB重建算法，并分发编码算法； （2）衍生，实现和表征新的Helical CB重建算法，这些算法提供具有各向同性空间分辨率和高局部时间分辨率（<300 ms）的3D图像； （3）为了得出，实施和表征新的Helical CB重建算法，这些算法提供了具有各向同性空间分辨率的3D图像，低对比度细节的高可检测性（可能是以时间分辨率为代价）。 间接地，该项目将对医学成像的各个方面产生重大影响，尤其是在肿瘤学，血管造影，感染和心脏疾病，创伤和放射疗法方面。