Data Consistency Based Motion Artifact Reduction for Head CT

基于数据一致性的头部 CT 运动伪影减少

• 批准号: 7384161
• 负责人: Hengyong Yu
• 金额: $ 7.85万
• 依托单位: VIRGINIA POLYTECHNIC INST AND ST UNIV
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2009-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7384161
• 关键词: Algorithms; Allergic Reaction; Automobile Driving; Biomedical Research; Blur; Child; Childhood; Clinical; Collaborations; Compatible; Condition; Data; Detection; Diagnosis; Diagnostic; Future; Goals; Head; Healthcare; Image; Intravenous; Lead; Medical; Methods; Modeling; Monitor; Morphologic artifacts; Motion; Noise; Numbers; Patients; Pattern; Performance; Physiological; Process; Radiation; Radiation Dosage; Resolution; Retinal Cone; Roentgen Rays; Rotation; Scanning; Sedation procedure; Slice; Solid; Solutions; Source; Specific qualifier value; System; Techniques; Testing; Time; Translating; Translations; United States National Institutes of Health; Validation; Virginia; Work; base; clinical application; cost; design; feeding; follow-up; image reconstruction; improved; indexing; instrument; interest; novel; prevent; reconstruction; research study; simulation

DESCRIPTION (provided by applicant): Most of routine CT methods assume that a subject being imaged is stationary during the scan. In important clinical applications and biomedical researches, such as pediatric head CT, the patient-motion is often unavoidable, leading to significant motion artifacts. The long-term goal of this project is to develop effective CT methods for motion estimation based image reconstruction, improve the diagnostic performance, and enable new clinical applications. Because motion artifact reduction has been a major problem in CT, our proposed work may have a significant impact on the healthcare by producing better image quality and extracting physiological and pathological features more accurately. In this R03 project, we will focus on the circular scanning trajectory and in-plane head motion, which is not only a satisfactory model in the cases we are interested but also a solid basis for our future study on more complicated motion patterns and scan modes. The specific aims are to (1) develop motion models and estimate the corresponding parameters from fan-beam/multi-slice data collected along a circular locus to describe the in-plane motion precisely; (2) adapt generalized cone-beam reconstruction methods to reconstruct a moving object in the fan-beam/multi-slice geometry; and (3) evaluate the proposed methods in numerical simulations, phantom experiments and retrospective patient studies. On completion, the proposed techniques will have been optimized, and their superior performance demonstrated in numerical simulation, phantom experiments and clinical applications. Using our proposed methods, the motion-induced blurring will have been reduced down to at least 30% of that associated with the current commercial methods of choice in the representative cases. This project will generate pilot data for a follow-up NIH R01 proposal targeting dynamic CT with noncircular scanning and general subject motion.Project Narrative: Motion artifact reduction has been a major problem in CT. Our project will develop a novel and effective solution to this long-standing problem, and may produce significantly better image quality to extract physiological and pathological features more accurately and more robustly. Hence, the proposed techniques promise to be translated for clinical use and should generate great healthcare benefits, especially for children.

描述（由申请人提供）：大多数常规CT方法假设被成像的受试者在扫描期间是静止的。在重要的临床应用和生物医学研究中，如儿童头部CT，患者运动往往是不可避免的，导致显着的运动伪影。该项目的长期目标是开发有效的CT方法，用于基于运动估计的图像重建，提高诊断性能，并实现新的临床应用。由于运动伪影减少一直是CT的一个主要问题，我们提出的工作可能会产生更好的图像质量和更准确地提取生理和病理特征的医疗保健产生重大影响。 在R 03项目中，我们将重点研究圆形扫描轨迹和平面内头部运动，这不仅是一个令人满意的模型，在我们感兴趣的情况下，也是一个坚实的基础，我们未来的研究更复杂的运动模式和扫描模式。具体目标是：（1）开发运动模型，并从沿沿着圆形轨迹收集的扇形束/多切片数据中估计相应参数，以精确描述平面内运动;（2）采用广义锥束重建方法，以重建扇形束/多切片几何结构中的运动物体;以及（3）在数值模拟、体模实验和回顾性患者研究中评估所提出的方法。 完成后，所提出的技术将被优化，其上级性能在数值模拟，体模实验和临床应用中得到证明。使用我们提出的方法，运动引起的模糊将被减少到至少30%，与目前的商业方法的选择在代表性的情况下。该项目将为后续NIH R 01提案生成试点数据，该提案针对具有非圆形扫描和一般受试者运动的动态CT。项目叙述： 减少运动伪影一直是CT中的一个主要问题。我们的项目将为这个长期存在的问题开发一种新颖有效的解决方案，并可能产生显着更好的图像质量，以更准确、更稳健地提取生理和病理特征。因此，所提出的技术有望转化为临床应用，并应产生巨大的医疗保健效益，特别是对儿童。