Evidence map›Paper›PMID 26158112›Full record

ArticleJournal of medical imaging (Bellingham, Wash.)2015

Content-based image retrieval in radiology: analysis of variability in human perception of similarity.

Jessica Faruque, Christopher F Beaulieu, Jarrett Rosenberg, Daniel L Rubin, Dorcas Yao, Sandy Napel

Abstract read
In one paragraph

Article in Journal of medical imaging (Bellingham, Wash.), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Jessica FaruqueStanford University , Department of Electrical Engineering, 350 Serra Mall, Stanford, California 94305, United States.
Christopher F BeaulieuStanford University Medical Center , Department of Radiology, 300 Pasteur Drive, Room S078, MC 5105, Stanford, California 94305, United States.
Jarrett RosenbergStanford University , Department of Radiology, Lucas MRS Imaging Center, 1201 Welch Road, Room P-280, Stanford, California 94305-5488, United States.
Daniel L RubinStanford University , Departments of Radiology and Medicine (Biomedical Informatics), Richard M. Lucas Center P285, 1201 Welch Road, Stanford, California 94305-5488, United States.
Dorcas YaoStanford University , Department of Radiology, 3801 Miranda Avenue, Palo Alto, California 94304-1290, United States.
Sandy NapelStanford University , Department of Radiology, James H. Clark Center, 318 Campus Drive, W3.1, Stanford, California 94305-5441, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We aim to develop a better understanding of perception of similarity in focal computed tomography (CT) liver images to determine the feasibility of techniques for developing reference sets for training and validating content-based image retrieval systems. In an observer study, four radiologists and six nonradiologists assessed overall similarity and similarity in 5 image features in 136 pairs of focal CT liver lesions. We computed intra- and inter-reader agreements in these similarity ratings and viewed the distributions of the ratings. The readers' ratings of overall similarity and similarity in each feature primarily appeared to be bimodally distributed. Median Kappa scores for intra-reader agreement ranged from 0.57 to 0.86 in the five features and from 0.72 to 0.82 for overall similarity. Median Kappa scores for inter-reader agreement ranged from 0.24 to 0.58 in the five features and were 0.39 for overall similarity. There was no significant difference in agreement for radiologists and nonradiologists. Our results show that developing perceptual similarity reference standards is a complex task. Moderate to high inter-reader variability precludes ease of dividing up the workload of rating perceptual similarity among many readers, while low intra-reader variability may make it possible to acquire large volumes of data by asking readers to view image pairs over many sessions.

Indexed as

computed tomographycontent-based image retrievalliverperceptionreference standardssimilarity

Identifiers

PMID26158112
PMCPMC4478987

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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.