Literature DB >> 31131292

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

Alexandre Ba1, Craig K Abbey2, Damien Racine1, Anaïs Viry1, Francis R Verdun1, Sabine Schmidt3, François O Bochud1.   

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.

Entities:  

Keywords:  channelized Hotelling observers; computed tomography; image quality; liver; observer performance

Year:  2019        PMID: 31131292      PMCID: PMC6527401          DOI: 10.1117/1.JMI.6.2.025501

Source DB:  PubMed          Journal:  J Med Imaging (Bellingham)        ISSN: 2329-4302


  26 in total

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Authors:  F O Bochud; J F Valley; F R Verdun; C Hessler; P Schnyder
Journal:  Med Phys       Date:  1999-07       Impact factor: 4.071

2.  Validating the use of channels to estimate the ideal linear observer.

Authors:  Brandon D Gallas; Harrison H Barrett
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3.  Receiver operating characteristic rating analysis. Generalization to the population of readers and patients with the jackknife method.

Authors:  D D Dorfman; K S Berbaum; C E Metz
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4.  A comparison of human and model observers in multislice LROC studies.

Authors:  Howard C Gifford; Michael A King; P Hendrik Pretorius; R Glenn Wells
Journal:  IEEE Trans Med Imaging       Date:  2005-02       Impact factor: 10.048

5.  A comparison of the Dorfman-Berbaum-Metz and Obuchowski-Rockette methods for receiver operating characteristic (ROC) data.

Authors:  Stephen L Hillis; Nancy A Obuchowski; Kevin M Schartz; Kevin S Berbaum
Journal:  Stat Med       Date:  2005-05-30       Impact factor: 2.373

6.  Insertion of virtual pulmonary nodules in CT data of the chest: development of a software tool.

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Journal:  Eur Radiol       Date:  2006-07-04       Impact factor: 5.315

7.  A comparison of denominator degrees of freedom methods for multiple observer ROC analysis.

Authors:  Stephen L Hillis
Journal:  Stat Med       Date:  2007-02-10       Impact factor: 2.373

8.  Recent developments in the Dorfman-Berbaum-Metz procedure for multireader ROC study analysis.

Authors:  Stephen L Hillis; Kevin S Berbaum; Charles E Metz
Journal:  Acad Radiol       Date:  2008-05       Impact factor: 3.173

9.  Channelized Hotelling observers for the assessment of volumetric imaging data sets.

Authors:  Ljiljana Platiša; Bart Goossens; Ewout Vansteenkiste; Subok Park; Brandon D Gallas; Aldo Badano; Wilfried Philips
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2011-06-01       Impact factor: 2.129

10.  Human- and model-observer performance in ramp-spectrum noise: effects of regularization and object variability.

Authors:  C K Abbey; H H Barrett
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2001-03       Impact factor: 2.129

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  2 in total

1.  Deep-learning model observer for a low-contrast hepatic metastases localization task in computed tomography.

Authors:  Hao Gong; Joel G Fletcher; Jay P Heiken; Michael L Wells; Shuai Leng; Cynthia H McCollough; Lifeng Yu
Journal:  Med Phys       Date:  2021-12-01       Impact factor: 4.506

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

Authors:  Juliane Conzelmann; Ulrich Genske; Arthur Emig; Michael Scheel; Bernd Hamm; Paul Jahnke
Journal:  Eur Radiol       Date:  2021-09-02       Impact factor: 5.315

  2 in total

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