Ba Alexandre, Abbey Craig K, Racine Damien, Viry Anaïs, Verdun Francis R, Schmidt Sabine, Bochud François O
Lausanne University Hospital and Lausanne University, Institute of Radiation Physics, Lausanne, Switzerland.
UC Santa Barbara, Department of Psychological and Brain Sciences, California, United States.
J Med Imaging (Bellingham). 2019 Apr;6(2):025501. doi: 10.1117/1.JMI.6.2.025501. Epub 2019 May 20.
Task-based image quality procedures in CT that substitute a human observer with a model observer usually use single-slice images with uniform backgrounds from homogeneous phantoms. However, anatomical structures and inhomogeneities in organs generate noise that can affect the detection performance of human observers. The purpose of this work was to assess the impact of background type, uniform or liver, and the viewing modality, single- or multislice, on the detection performance of human and model observers. We collected abdominal CT scans from patients and homogeneous phantom scans in which we digitally inserted low-contrast signals that mimicked a liver lesion. We ran a rating experiment with the two background conditions with three signal sizes and three human observers presenting images in two reading modalities: single- and multislice. In addition, channelized Hotelling observers (CHO) for single- and multislice detection were implemented and evaluated according to their degree of correlation with the human observer performance. For human observers, there was a small but significant improvement in performance with multislice compared to the single-slice viewing mode. Our data did not reveal a significant difference between uniform and anatomical backgrounds. Model observers demonstrated a good correlation with human observers for both viewing modalities. Human observers have very similar performances in both multi- and single-slice viewing mode. It is therefore preferable to use single-slice CHO as this model is computationally more tractable than multislice CHO. However, using images from a homogeneous phantom can result in overestimating image quality as CHO performance tends to be higher in uniform than anatomical backgrounds, while human observers have similar detection performances.
CT中基于任务的图像质量评估程序通常用模型观察者替代人类观察者,这些程序通常使用来自均匀体模的具有均匀背景的单层面图像。然而,器官中的解剖结构和不均匀性会产生噪声,这可能会影响人类观察者的检测性能。本研究的目的是评估背景类型(均匀或肝脏)和观察方式(单层或多层)对人类和模型观察者检测性能的影响。我们收集了患者的腹部CT扫描图像以及均匀体模扫描图像,在体模扫描图像中我们通过数字方式插入了模拟肝脏病变的低对比度信号。我们进行了一项评级实验,设置了两种背景条件、三种信号大小,并让三名人类观察者以两种读片方式呈现图像:单层和多层。此外,还实现了用于单层和多层检测的通道化霍特林观察者(CHO),并根据它们与人类观察者性能的相关程度进行评估。对于人类观察者而言,与单层观察模式相比,多层观察模式下的性能有小幅但显著的提升。我们的数据并未显示均匀背景和解剖背景之间存在显著差异。对于两种观察方式,模型观察者与人类观察者都表现出良好的相关性。人类观察者在多层和单层观察模式下的表现非常相似。因此,最好使用单层CHO,因为该模型在计算上比多层CHO更易于处理。然而,使用来自均匀体模的图像可能会高估图像质量,因为在均匀背景下CHO的性能往往高于解剖背景,而人类观察者的检测性能相似。