Basic Research for the Development of Helical Cone-Beam CT

螺旋锥束CT发展的基础研究

• 批准号: 13650452
• 负责人: KUDO Hiroyuki
• 金额: $ 1.41万
• 依托单位: University of Tsukuba
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 2001
• 资助国家: 日本
• 起止时间: 2001 至 2002
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-13650452/
• 关键词: CT; Cone-Beam; Image Reconstruction; Angiography; Micro CT; Helical; Medical Imaging; Image Processing; 放射線医学

Cone-beam helical CT (based on combining the cone-beam x-ray exposure and the helical scanning) is receiving increased attention as a future fast 3-D CT. However, enough basic researches are not performed in the current stage about its scanner design and image reconstruction. The aim of this research project is to investigate the following three points which are important to develop helical cone-beam CT scanners. First, we developed an efficient scanner design method which is based on arranging detector elements very efficiently. This allows us to scan the patient with a large (maximum) helical pitch even in the case where the number of detector elements are limited. Next, we developed the following two types of image reconstruction methods. The first type aims at using in commercial helical cone-beam CT scanners. These include an exact algorithm based on the 3-D Radon inversion and an approximate (but very fast) algorithm based on rebinning cone-beam data into fan-beam data. The second type aims at using in angiography and micro-CT systems. The algorithm is an algebraic one which is based on the duality of non-linear programming. During the. development of these algorithms, we also obtained two important insights about basic mathematics of CT image reconstruction. These include a super-short-scan image reconstruction and a new exact cone-beam reconstruction method for general source trajectory. Finally, as an application to real data, we applied the developed algebraic reconstruction algorithm to the micro-CT system at Marquette university. The result demonstrates that it is possible to reconstruct a high-quality 3-D image of a rat lung (confined within a cube of side 2cm) from only 8 projections with the developed algorithm.

锥束螺旋 CT（基于锥束 X 射线曝光和螺旋扫描的结合）作为未来的快速 3-D CT 受到越来越多的关注。然而，现阶段对其扫描仪设计和图像重建还没有进行足够的基础研究。本研究项目的目的是研究以下三点，这对于开发螺旋锥形束 CT 扫描仪很重要。首先，我们开发了一种高效的扫描仪设计方法，该方法基于非常有效地布置探测器元件。即使在探测器元件数量有限的情况下，这也使我们能够以大（最大）螺距扫描患者。接下来，我们开发了以下两种类型的图像重建方法。第一种类型旨在用于商用螺旋锥形束 CT 扫描仪。其中包括基于 3-D Radon 反演的精确算法和基于将锥形束数据重新分类为扇形束数据的近似（但非常快）算法。第二种类型旨在用于血管造影和显微CT系统。该算法是一种基于非线性规划的对偶性的代数算法。期间。通过这些算法的发展，我们还获得了关于 CT 图像重建基础数学的两个重要见解。其中包括超短扫描图像重建和用于一般源轨迹的新的精确锥束重建方法。最后，作为实际数据的应用，我们将开发的代数重建算法应用到马凯特大学的显微CT系统中。结果表明，利用所开发的算法，仅通过 8 个投影即可重建大鼠肺部（限制在边长 2 厘米的立方体内）的高质量 3D 图像。