Evidence map›Paper›PMID 31131292›Full record

ArticleJournal of medical imaging (Bellingham, Wash.)2019

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

Alexandre Ba, Craig K Abbey, Damien Racine, Anaïs Viry, Francis R Verdun, Sabine Schmidt, François O Bochud

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Article in Journal of medical imaging (Bellingham, Wash.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Alexandre BaLausanne University Hospital and Lausanne University, Institute of Radiation Physics, Lausanne, Switzerland.
Craig K AbbeyUC Santa Barbara, Department of Psychological and Brain Sciences, California, United States.
Damien RacineLausanne University Hospital and Lausanne University, Institute of Radiation Physics, Lausanne, Switzerland.
Anaïs ViryLausanne University Hospital and Lausanne University, Institute of Radiation Physics, Lausanne, Switzerland.
Francis R VerdunLausanne University Hospital and Lausanne University, Institute of Radiation Physics, Lausanne, Switzerland.
Sabine SchmidtLausanne University Hospital and Lausanne University, Department of Radiology, Lausanne, Switzerland.
François O BochudLausanne University Hospital and Lausanne University, Institute of Radiation Physics, Lausanne, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

channelized Hotelling observerscomputed tomographyimage qualityliverobserver performance

Identifiers

PMID31131292
PMCPMC6527401

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.