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锥形束计算机断层扫描中的源探测器轨迹优化:当前技术的全面综述。

Source-detector trajectory optimization in cone-beam computed tomography: a comprehensive review on today's state-of-the-art.

机构信息

Austrian Center for Medical Innovation and Technology (ACMIT), Wiener Neustadt, Austria.

Research center for Medical Image Analysis and Artificial Intelligence (MIAAI), Department of Medicine, Danube Private University, Krems, Austria.

出版信息

Phys Med Biol. 2022 Aug 16;67(16). doi: 10.1088/1361-6560/ac8590.

Abstract

Cone-beam computed tomography (CBCT) imaging is becoming increasingly important for a wide range of applications such as image-guided surgery, image-guided radiation therapy as well as diagnostic imaging such as breast and orthopaedic imaging. The potential benefits of non-circular source-detector trajectories was recognized in early work to improve the completeness of CBCT sampling and extend the field of view (FOV). Another important feature of interventional imaging is that prior knowledge of patient anatomy such as a preoperative CBCT or prior CT is commonly available. This provides the opportunity to integrate such prior information into the image acquisition process by customized CBCT source-detector trajectories. Such customized trajectories can be designed in order to optimize task-specific imaging performance, providing intervention or patient-specific imaging settings. The recently developed robotic CBCT C-arms as well as novel multi-source CBCT imaging systems with additional degrees of freedom provide the possibility to largely expand the scanning geometries beyond the conventional circular source-detector trajectory. This recent development has inspired the research community to innovate enhanced image quality by modifying image geometry, as opposed to hardware or algorithms. The recently proposed techniques in this field facilitate image quality improvement, FOV extension, radiation dose reduction, metal artifact reduction as well as 3D imaging under kinematic constraints. Because of the great practical value and the increasing importance of CBCT imaging in image-guided therapy for clinical and preclinical applications as well as in industry, this paper focuses on the review and discussion of the available literature in the CBCT trajectory optimization field. To the best of our knowledge, this paper is the first study that provides an exhaustive literature review regarding customized CBCT algorithms and tries to update the community with the clarification of in-depth information on the current progress and future trends.

摘要

锥形束计算机断层扫描(CBCT)成像在广泛的应用中变得越来越重要,例如图像引导手术、图像引导放射治疗以及诊断成像,如乳腺和骨科成像。在早期工作中就认识到非圆形源探测器轨迹的潜在好处,以提高 CBCT 采样的完整性并扩展视野(FOV)。介入成像的另一个重要特点是,患者解剖结构的先验知识,如术前 CBCT 或之前的 CT 通常是可用的。这为通过定制 CBCT 源探测器轨迹将此类先验信息集成到图像采集过程中提供了机会。可以设计这种定制轨迹,以便优化特定任务的成像性能,提供介入或患者特定的成像设置。最近开发的机器人 CBCT C 臂以及具有额外自由度的新型多源 CBCT 成像系统提供了在传统的圆形源探测器轨迹之外,在很大程度上扩展扫描几何形状的可能性。这一最新发展激发了研究界通过修改图像几何形状而不是硬件或算法来创新增强图像质量的灵感。该领域最近提出的技术促进了图像质量的提高、视野的扩展、辐射剂量的减少、金属伪影的减少以及在运动学约束下的 3D 成像。由于 CBCT 成像在临床和临床前应用以及工业中的图像引导治疗中的巨大实用价值和日益重要性,本文重点回顾和讨论 CBCT 轨迹优化领域的现有文献。据我们所知,这是第一篇提供有关定制 CBCT 算法的全面文献综述的研究,并试图通过澄清有关当前进展和未来趋势的深入信息来更新社区。

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