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Objective image quality assessment for positron emission tomography: Planar (two-dimensional) and volumetric (three-dimensional) human and model observer studies.

机译:正电子发射断层扫描的客观图像质量评估:平面(二维)和体积(三维)人类和模型观察者研究。

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The quantitative assessment of medical image quality should be tied to specific tasks. The use of receiver operating characteristic (ROC) studies to analyze human observer performance is considered the ‘gold standard’ for detection task studies. These studies, however, require considerable time and effort and so are not well-suited for parameter optimization. Thus there is considerable interest in developing mathematical ‘model’ observers that mimic the performance of human observers.; The detection task is an essential component of Positron Emission Tomography (PET) imaging, which is routinely used for the detection and staging of cancer. PET imaging systems acquire and reconstruct tomographic images as contiguous volumetric (3D) images. Physicians typically interpret these images by searching the image volume using volumetric displays (showing linked transverse, coronal and sagittal sections of the image volume). Most observer studies, however, typically use planar images for evaluation with both human and model observers.; This dissertation proposes a volumetric model observer computation method, and investigates differences between planar (2D) and volumetric (3D) model observer performances and their correlation with human observer performance for PET imaging. Multiple sinogram realizations were simulated with statistically accurate noise properties. Sinograms were corrected for attenuation and background coincidences, and reconstructed with filtered backprojection (FBP) into image volumes. The apodizing filter used for FBP was the Hanning window. For human observer ROC studies, an observer scoring software tool, similar to the volumetric display being used in clinical PET imaging, was developed. For model observer studies, the non-prewhitening matched filter (NPWMF) and the channelized Hotelling observer (CHO) were used, in both 2D and 3D implementations.; The 3D NPWMF and the CHO model observers yielded significantly higher detectabilities than the 2D model observers, and had higher correlations with human performance than the 2D versions. When the axial smoothing was applied to achieve isotropic target resolution, however, performance differences between the 2D and the 3D model observers were not significant.; Because of their high correlations with human performance, the volumetric model observers, especially the 3D CHO, can be used as surrogates for measuring human performance, in particular for optimizing free parameters for cancer detection with whole-body PET imaging.
机译:医学图像质量的定量评估应与特定任务联系在一起。使用接收器工作特性(ROC)研究来分析人类观察者的表现被认为是检测任务研究的“黄金标准”。但是,这些研究需要大量的时间和精力,因此不适用于参数优化。因此,开发模拟人类观察者表现的数学“模型”观察者引起了极大的兴趣。检测任务是正电子发射断层扫描(PET)成像的基本组成部分,通常用于检测和分期癌症。 PET成像系统获取断层图像并将其重建为连续的体积(3D)图像。医师通常通过使用体积显示(显示图像体积的链接的横向,冠状和矢状切面)搜索图像体积来解释这些图像。但是,大多数观察者研究通常都使用平面图像对人类和模型观察者进行评估。本文提出了一种体积模型观测器的计算方法,并研究了平面(2D)和体积(3D)模型观测器性能之间的差异以及它们与人类PET成像观察器性能的相关性。使用统计准确的噪声属性模拟了多个正弦图实现。对Singram进行了衰减和背景重合的校正,并使用滤波反投影(FBP)将其重建为图像体积。用于FBP的变迹过滤器是Hanning窗口。对于人类观察者ROC研究,开发了一种观察者评分软件工具,类似于临床PET成像中使用的体积显示。对于模型观察者研究,在2D和3D实现中均使用了非预白化匹配滤波器(NPWMF)和信道化的Hotelling观察者(CHO)。 3D NPWMF和CHO模型观察者比2D模型观察者具有更高的可检测性,并且与人类性能的相关性高于2D版本。但是,当应用轴向平滑以实现各向同性目标分辨率时,2D和3D模型观察者之间的性能差异并不明显。由于体积模型观察者(尤其是3D CHO)与人类绩效的相关性很高,因此可以用作替代指标来测量人类绩效,尤其是优化用于全身PET成像检测癌症的自由参数。

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