Development of Methods and Software for Interior Tomography Applications

描述（由申请人提供）：与内部问题没有唯一解决方案的传统观点相反，在2007年，我们开发了内部层析成像技术并获得专利（根据仅与通过内部感兴趣区域的线相关联的X射线投影数据进行精确且稳定的内部重建）。当将常规CT算法应用于这种不完整的数据集时，ROI外部的特征可能会在真实的特征内部产生重叠的伪影。我们的新的内部重建理论假设在一个小的子区域的利益，如在肺部的空气，在心脏的血液等，作为一个令人惊讶的结果，准确和稳定的内部重建成为可行的知识！这一突破具有许多生物医学意义，并将有利于或实现广泛的CT应用，包括肺部CT、心脏CT、颞骨成像、术中CT等，其中我们需要处理大型物体、最小化辐射剂量、抑制散射伪影、增强时间分辨率、降低系统成本并增加扫描仪吞吐量。该项目的总体目标是开发内部层析成像的解析和迭代重建算法和软件。具体目标是：（1）开发以前不可能的分析和理论上精确的内部重建算法;（2）开发有效的迭代内部重建算法，该算法包含额外的约束，以提高图像质量并进一步降低辐射剂量;以及（3）在数值模拟和体模实验中评估所提出的内部重建算法，并开发第一个同类软件用于内部断层扫描的包装。在这个项目完成后，我们将开发分析和迭代精确内部重建算法的临床前和临床CT应用，并开发一个商业软件包准备在市场上具有竞争力。公共卫生相关性：2007年，我们开发了内部断层扫描技术并获得专利（根据X射线投影数据进行精确稳定的内部重建，仅与通过内部感兴趣区域的线条相关）。我们的理论假设对感兴趣区域中的一个小的子区域（例如肺中的空气、心脏中的血液等）有精确的了解，因此，第一次精确和稳定的内部重建成为现实。我们提出的方法和软件将有利于或使广泛的CT应用，包括肺部CT，心脏CT，颞骨成像，术中CT等，在那里我们需要处理大的对象，最小化辐射剂量，抑制散射伪影，提高时间分辨率，降低系统成本，并增加扫描仪的吞吐量。

DESCRIPTION (provided by applicant): In contrast to the conventional wisdom that the interior problem does not have a unique solution, in 2007 we developed and patented the interior tomography technology (exact and stable interior reconstruction from x-ray projection data associated with only lines through an internal region of interest). When applying conventional CT algorithms to such an incomplete dataset, the features outside the ROI may create artifacts overlapping inside real features. Our new interior reconstruction theory assumes exact knowledge on a small subregion in the region of interest, such as air in the lungs, blood in the heart, etc. As a surprising result, exact and stable interior reconstruction becomes feasible! This break though has numerous biomedical implications, and will benefit or enable a wide range of CT applications including lung CT, cardiac CT, temporal bone imaging, intraoperative CT and so on, where we need to handle large objects, minimize radiation dose, suppress scattering artifacts, enhance temporal resolution, reduce system cost, and increase scanner throughput. The overall goal of this project is to develop both analytic and iterative reconstruction algorithms and software for interior tomography. The specific aims are to (1) develop analytic and theoretically exact interior reconstruction algorithms that have not been possible before; (2) develop efficient iterative interior reconstruction algorithms that incorporate additional constraints to improve image quality and reduce radiation dose further; and (3) evaluate the proposed interior reconstruction algorithms in numerical simulation and phantom experiments and develop the first of its kind software package for interior tomography. On completion of this project, we will have developed both analytic and iterative exact interior reconstruction algorithms for preclinical and clinical CT applications, and develop a commercial software package ready to be competitive on the marketplace. PUBLIC HEALTH RELEVANCE: In 2007 we developed and patented the interior tomography technology (exact and stable interior reconstruction from x-ray projection data associated with only lines through an internal region of interest). Our theory assumes exact knowledge on a small subregion in the region of interest, such as air in the lungs, blood in the heart, etc., so that for the first time exact and stable interior reconstruction becomes realistic. Our proposed methods and software will benefit or enable a wide range of CT applications including lung CT, cardiac CT, temporal bone imaging, intraoperative CT and so on, where we need to handle large objects, minimize radiation dose, suppress scattering artifacts, enhance temporal resolution, reduce system cost, and increase scanner throughput.