Cone-Beam Methods for Dynamic Volumetric X-Ray CT

描述(由申请人提供)： 目前，医用CT扫描仪发展迅速，锥角越来越大，而生物医学微型CT扫描仪已经处于锥束几何形状。尽管锥束CT很重要，但锥束图像重建算法还没有得到充分的发展。迫切需要锥束CT的动态体积性能，受剂量、噪声、范围、对比度等多种限制。该项目的总体目标是开发和优化解析锥束算法，重点是高时间分辨率和短扫描范围，并直接适用于心脏成像、CT透视、灌注研究、CT血管成像、肿瘤学成像、小动物成像以及PET和SPECT等主要应用。该项目基于最新的锥束CT结果，分别在Feldkamp型、Grangeat型和Katsevich型框架中进行近似重建和精确重建。具体目标是：(1)通过扫描方向图设计和加权方案优化，改进Feldkamp类算法；(2)通过修正锥束数据，扩展Grangate型半扫描算法用于长目标重建，并将基于Radon空间的重建转换为滤波反投影格式；(3)通过检测覆盖最小化和基于n-PI几何的公式，改进Katsevich类动态重建算法；(4)在理论分析、数值模拟和体模实验中对所提出的锥束算法进行评估和验证，并在小鼠和患者实验中验证其可行性和实用性。完成后，将系统地开发出用于动态体积CT和微型CT的优秀和实用的锥束算法，并具有良好的图像质量。这些提出的算法将在PC集群上实现。这些算法的优势将在小鼠和患者的研究中得到证明。

DESCRIPTION (provided by applicant): Currently, medical CT scanners are under rapid development with an increasingly larger cone angle, while biomedical micro-CT scanners are already in cone-beam geometry. Despite the importance of cone-beam CT, cone-beam image reconstruction algorithms are not fully developed. There is a critical and immediate need for a dynamic volumetric performance of cone-beam CT, subject to multiple constraints such as dose, noise, range, contrast, etc. The overall goal of this project is to develop and optimize analytic cone-beam algorithms with an emphasis on high temporal resolution and short scan range, and directly applicable to major applications such as cardiac imaging, CT fluoroscopy, perfusion studies, CT angiography, oncologic imaging, small animal imaging, as well as PET and SPECT. This project is based on the latest cone-beam CT results, and focuses on both approximate and exact reconstruction in the Feldkamp-type, Grangeat-type and Katsevich-type frameworks respectively. The specific aims are to (1) improve Feldkamp-type algorithms for less than half-scan data by scanning pattern design and weighting scheme optimization; (2) extend Grangeat-type half-scan algorithms for long object reconstruction by correcting cone-beam data, and transform the Radon space based reconstruction into the filtered backprojection format; (3) modify Katsevich-type algorithms for dynamic reconstruction by detection coverage minimization and n-PI geometry-based formulation; and (4) evaluate and validate the proposed cone-beam algorithms in theoretical analysis, numerical simulation and phantom experiments, and demonstrate their feasibility and utilities in mouse and patient studies. On completion, superior and practical cone-beam algorithms will have been systematically developed with excellent image quality for dynamic volumetric CT and micro-CT. These proposed algorithms will have been implemented on a PC cluster. The advantages of the algorithms will have been demonstrated in mouse and patient studies.