20 May 2019 Channelized Hotelling observer correlation with human observers for low-contrast detection in liver CT images
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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 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.
© 2019 Society of Photo-Optical Instrumentation Engineers (SPIE) 2329-4302/2019/$25.00 © 2019 SPIE
Alexandre Ba, Craig K. Abbey, Damien Racine, Anaïs Viry, Francis R. Verdun, Sabine Schmidt, and François O. Bochud "Channelized Hotelling observer correlation with human observers for low-contrast detection in liver CT images," Journal of Medical Imaging 6(2), 025501 (20 May 2019). https://doi.org/10.1117/1.JMI.6.2.025501
Received: 7 October 2018; Accepted: 15 April 2019; Published: 20 May 2019
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Cited by 5 scholarly publications.
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KEYWORDS
Computed tomography

Liver

Image quality

Signal detection

Performance modeling

Spatial frequencies

Medical imaging

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