Iterative Image reconstruction for high-resolution PET imaging

高分辨率 PET 成像的迭代图像重建

• 批准号: 7383846
• 负责人: JINYI QI
• 金额: $ 19.74万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-04-01 至 2010-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7383846
• 关键词: Adopted; Algorithms; Animal Experiments; Animal Model; Animals; Back; Biological; Biological Models; Biology; Class; Clinical; Code; Computer Simulation; Condition; Detection; Emission-Computed Tomography; Functional Imaging; Funding; Goals; Grant; Image; Lesion; Magnetic Resonance Imaging; Medical Imaging; Methods; Modality; Modeling; Morphologic artifacts; Noise; Optical Tomography; Other Imaging Modalities; Performance; Photons; Positron-Emission Tomography; Research; Resolution; Scanning; Small Animal Imaging Resource Programs; System; Time; Validation; Work; X-Ray Computed Tomography; X-Ray Tomography; abstracting; animal data; base; human disease; image reconstruction; improved; innovation; novel; reconstruction; research study; simulation; success; theories; time use; tomography

DESCRIPTION (provided by applicant): Iterative reconstruction algorithms that significantly improve image quality over filtered backprojection methods have been developed for emission tomography. However, most current reconstruction algorithms implicitly assume that the system model is exact. The daunting computational challenge associated with the direct use of an exact system model in each forward and back projection has often led people to adopt less accurate models. This results in increased noise and reduced resolution in reconstructed images, because the effect of the modeling error cannot be corrected in the existing methods. The goal of this grant is to develop a new class of iterative reconstruction methods that can compensate the effect of modeling error. The work is based on our thorough analysis of error propagation from each component in the system model into reconstructed images. The innovation of the new method is that it does not require an exact system model in every forward and back projection. The method can obtain high-resolution images when direct use of an accurate system model in the iterative reconstruction is impractical, and it can also reduce reconstruction time by using simplified fast forward and back projectors without sacrificing image quality. We will first develop the theory of high-resolution iterative image reconstruction with error correction capability. Then we will focus on the application and validation of the theory in positron emission tomography (PET). We will implement new reconstruction algorithms on microPET scanners, and will evaluate the lesion detection and quantitation performance using Monte Carlo simulations, physical phantom experiments, and real animal data. We believe that the new algorithms will provide high-resolution images and accurate quantitative information for understanding human diseases in small animal models. Upon success, we will extend the reconstruction algorithm to clinical imaging systems and will also apply the theory to other imaging modalities, such as X-ray CT, SPECT, MRI, and optical tomography. Lay abstract: Positron emission tomography (PET) is a functional imaging modality that is widely used in clinical and biological studies. This project will develop a novel image reconstruction method for PET which will provide high-resolution images and accurate quantitative information for understanding and treating human diseases.

描述（由申请人提供）：已经开发出用于发射断层扫描的迭代重建算法，其相对于滤波反投影方法显着提高图像质量。然而，大多数当前的重建算法隐含地假设系统模型是精确的。在每个正向和反向投影中直接使用精确的系统模型所带来的艰巨的计算挑战常常导致人们采用不太准确的模型。这导致重建图像中的噪声增加和分辨率降低，因为现有方法无法纠正建模误差的影响。该资助的目标是开发一类新的迭代重建方法，可以补偿建模误差的影响。这项工作基于我们对从系统模型中每个组件到重建图像的误差传播的全面分析。新方法的创新之处在于，它不需要在每次正向和反向投影中都建立精确的系统模型。当在迭代重建中直接使用精确的系统模型不切实际时，该方法可以获得高分辨率图像，并且还可以通过使用简化的快速前向和后向投影仪来减少重建时间，而不牺牲图像质量。我们将首先发展具有纠错能力的高分辨率迭代图像重建理论。然后我们将重点关注该理论在正电子发射断层扫描（PET）中的应用和验证。我们将在 microPET 扫描仪上实施新的重建算法，并使用蒙特卡罗模拟、物理模型实验和真实动物数据来评估病变检测和定量性能。我们相信，新算法将为在小动物模型中了解人类疾病提供高分辨率图像和准确的定量信息。一旦成功，我们将把重建算法扩展到临床成像系统，并将该理论应用到其他成像模式，如 X 射线 CT、SPECT、MRI 和光学断层扫描。摘要：正电子发射断层扫描 (PET) 是一种广泛应用于临床和生物学研究的功能成像方式。该项目将开发一种新颖的 PET 图像重建方法，为理解和治疗人类疾病提供高分辨率图像和准确的定量信息。