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Do different radiologists perceive medical images the same way? Some insights from Representational Similarity Analysis

Scholary Output:
Contribution to journal
Conference article
Peer-review

Related Event

Title

2019 Human Vision and Electronic Imaging Conference, HVEI 2019

Event type

Conference

Date

01/13/2019 - 01/17/2019

Location

BurlingameUnited States

Abstract

Characterizing what experts perceive in medical images is a difficult problem, both because doing so requires somehow characterizing the internal mental representations of the observer, and because the underlying diagnostic information tends to be abstract and not readily describable in terms of well-defined image features. Representational Similarity Analysis (RSA) is a method originally developed in mathematical psychology that provides a theoretically sound and quantitative framework for measuring the mental representations of visual images in human observers. Here we used RSA to measure the extent to which the same underlying set of mammograms elicit similar mental representations in different practicing radiologists (N = 26). We found that the internal representations were statistically indistinguishable across different radiologists (p > 0.05). Moreover, the mental representations significantly parallel the diagnostic information in the images (p < 0.05 for each subject), indicating that various radiologists perceived the same set of diagnostic information in the underlying images. Together, these results indicate that medical images elicit similar mental representations in different radiologists.

Publication Information

Output type

Scholary Output:
Contribution to journal
Conference article
Peer-review

Original language

English (US)

Article number

HVEI-225

Journal (Volume, Issue Number)

IS and T International Symposium on Electronic Imaging Science and Technology (Volume 2019, Issue 12)

Publication milestones

  • Published - 01/13/2019

Publication status

Published - 01/13/2019

Publication IDs

  • Scopus: 85080049011

Publication metrics

Metrics

Scopus
citations
SciVal
FWCI
0.67
SciVal
Author count
2
SciVal
citations
1
SciVal
Paper percentile
49
Fractional count
1
Fractional count
0.50
Fractional count
1
Fractional count
0.50
Fractional count
1
Fractional count
1

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Citation count
2
Captures
2

Funding Details

We thank Ms. Fallon Branch for help with the preparation of this manuscript, and Ms. Jennevieve Sevilla for excellent technical assistance, and the National Cancer Institute (NCI) for funding our participation in the HVEI panel on medical image perception. We are grateful to the NCI and to Dr. Jeremy Wolfe of Harvard Medical School for organizing the aforementioned RSNA testing facility each year. This study was supported by Army Research Office (ARO) grants W911NF-11-1-0105 and W911NF-15-1-0311 to JH.