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

Jay Hegdé, Evgeniy Bart

Research output: Contribution to journalConference article

1 Scopus citations

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.

Original languageEnglish (US)
Article numberHVEI-225
JournalIS and T International Symposium on Electronic Imaging Science and Technology
Volume2019
Issue number12
DOIs
StatePublished - Jan 13 2019
Event2019 Human Vision and Electronic Imaging Conference, HVEI 2019 - Burlingame, United States
Duration: Jan 13 2019Jan 17 2019

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Human-Computer Interaction
  • Software
  • Electrical and Electronic Engineering
  • Atomic and Molecular Physics, and Optics

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