Cone-Beam Tomography with Truncated Projections

描述(由申请人提供)： 该项目的长期目标是解决锥束层析成像中的截断问题，并实现和自由分发适用于最常见的锥束成像配置的图像重建软件。 具体目的是：1)设计、实现和公开用于锥束计算机断层扫描(CBCT)几何图形的快速准确图像重建代码，其中源和探测器围绕患者旋转一次(或略多于一次)，并且投影总是轴向截断(并且也可以被轴向截断)；2)设计、实现和公开可用于CBCT几何图形的快速准确图像重建代码，所述CBCT几何图形是为基于C臂的CT定制的，投影测量在大约180度的角度范围上，并且具有相关的截断图案，3)设计和实现简单实用的几何重建参数自动获取方法，并将这些参数传递给AIMS 1和AIMS 2扫描仪结构的重建算法。 这些方法包括设计不受错误信息传播影响的算法，错误信息通常伴随着截断的投影数据。将考虑六种锥束结构，并将通过组合在过去成功地解决某些特定锥束截断问题的基本数学工具来设计算法。这些算法将用计算机模拟数据和来自台式扫描仪和物理扫描仪的体模测量进行测试。将通过扩展现有的分析方法来设计自动校准，并使用模拟和真实数据对照卡方方法进行测试。 该项目的健康益处涉及锥束断层扫描从目前主要作为高对比度成像工具的状态转变为在图像指导和诊断中广泛应用的快速、定量、体积成像方式。

DESCRIPTION (provided by applicant): The long term objective of this project is to solve the truncation problem in cone-beam tomography, and to implement and freely distribute image reconstruction software suitable for the most common cone-beam imaging configurations. The specific aims are: 1) to devise, implement, and make publicly available, fast accurate image reconstruction code for cone-beam computed tomography (CBCT) geometries where the source and detector rotate once (or slightly more than once) about the patient, and the projections are always truncated axially (and may also be truncated transaxially), 2) to devise, implement, and make publicly available, fast accurate image reconstruction code for CBCT geometries tailored to C-arm based CT with projections measured over an angular range of about 180 degrees, and with relevant patterns of truncation, and 3) to design and implement simple practical calibration methods from which geometric reconstruction parameters are automatically obtained and passed to the reconstruction algorithms for the scanner configurations of aims 1 and 2. The methods involve devising algorithms that are impervious to the propagation of false information that is normally concomitant with truncated projection data. Six cone-beam configurations will be considered, and algorithms will be devised by assembling fundamental mathematical tools which have been successful in solving certain specific cone-beam truncation problems in the past. The algorithms will be tested with computer simulated data and phantom measurements from benchtop and physical scanners. Automated calibration will be devised by extending existing analytic approaches, and tested against chi-squared approaches using simulated and real data. The health benefits of this project relate to the transition of cone-beam tomography from its current status as primarily a high-contrast imaging tool to a fast, quantitative, volume imaging modality with widespread applications in image guidance and diagnosis.