Channelized Hotelling observer correlation with human observers for low-contrast detection in liver CT images

Abstract

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 singleslice 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.

Comparison of low-contrast detectability between uniform and anatomically realistic phantoms—influences on CT image quality assessment

“…Anatomical images had a low-frequency noise component that was predominant regardless of dose and image reconstruction mode. This component was in good agreement with reports of high NPS values at low spatial frequencies in patients [ 15 ]. Anatomical background structure also influenced the denoising power of AIDR 3D, which adds to reports on interactions between anatomical texture, noise, and spatial resolution when iterative reconstruction is applied [ 16 – 18 ].…”

Evaluation of low-contrast detectability of photon-counting-detector CT using channelized Hotelling observer and an ACR accreditation phantom

“…Channelized Hotelling observer (CHO) was proved to correlate with human observer performance in low-contrast detection, classification, and localization tasks in clinical CT [9][10][11][12][13][14][15]. In our previous study, we developed an efficient CHO model observer for accurate and precise measurement of low-contrast detectability with only 1-3 repeated scans on the most widely used ACR accreditation phantom [16].…”

Visual Search Performance and Strategy for Three-Dimensional Visualization Systems: Impact of Radiologist Experience

“…Numerous cross-sections of anatomical structures ensure a more detailed and comprehensive representation of visual information when compared to X-ray images [3,5], however, the complexity of three-dimensional visualization comes with benefits and costs. On the one hand, radiologists have the opportunity to detect the smallest details [2,4], which positively influences the identification of abnormal lesions [6]. On the 2 of 17 other hand, the limited processing capacity of the human visual system [7] is systematically challenged by the presentation of complex visual information on flat-panel displays.…”