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使用变焦 PET 系统进行病变检测的自适应成像。

Adaptive imaging for lesion detection using a zoom-in PET system.

机构信息

Department of Biomedical Engineering, University of California, Davis, CA 95616, USA.

出版信息

IEEE Trans Med Imaging. 2011 Jan;30(1):119-30. doi: 10.1109/TMI.2010.2064173. Epub 2010 Aug 9.

Abstract

Positron emission tomography (PET) has become a leading modality in molecular imaging. Demands for further improvements in spatial resolution and sensitivity remain high with growing number of applications. In this paper we present a novel PET system design that integrates a high-resolution depth-of-interaction (DOI) detector into an existing PET system to obtain higher-resolution and higher-sensitivity images in a target region around the face of the high-resolution detector. A unique feature of the proposed PET system is that the high-resolution detector can be adaptively positioned based on the detectability or quantitative accuracy of a feature of interest. This paper focuses on the signal-known-exactly, background-known-exactly (SKE-BKE) detection task. We perform theoretical analysis of lesion detectability using computer observers, and then develop methods that can efficiently calculate the optimal position of the high-resolution detector that maximizes the lesion detectability. We simulated incorporation of a high-resolution DOI detector into the microPET II scanner. Quantitative results verified that the new system has better performance than the microPET II scanner in terms of spatial resolution and lesion detectability, and that the optimal position for lesion detection can be reliably predicted by the proposed method.

摘要

正电子发射断层扫描(PET)已成为分子成像的主要手段。随着应用数量的增加,对提高空间分辨率和灵敏度的需求仍然很高。在本文中,我们提出了一种新的 PET 系统设计,该设计将高分辨率的深度感应(DOI)探测器集成到现有的 PET 系统中,以在高分辨率探测器表面的目标区域获得更高分辨率和更高灵敏度的图像。所提出的 PET 系统的一个独特特点是,高分辨率探测器可以根据感兴趣特征的可检测性或定量精度自适应地定位。本文重点介绍信号完全已知-背景完全已知(SKE-BKE)检测任务。我们使用计算机观察者对病变可检测性进行了理论分析,然后开发了可以有效地计算出最大化病变可检测性的最佳高分辨率探测器位置的方法。我们模拟了将高分辨率 DOI 探测器集成到 microPET II 扫描仪中。定量结果验证了新系统在空间分辨率和病变可检测性方面比 microPET II 扫描仪具有更好的性能,并且可以通过提出的方法可靠地预测病变检测的最佳位置。

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