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Published on: August 30, 2013
Inversion effects in the expert classification of mammograms and faces
Michael D Chin1, Karla K Evans2, Jeremy M Wolfe3
11Department of Psychology, University of Victoria, Victoria, BC Canada.
Expert radiologists use holistic perception to detect abnormalities in mammograms, similar to how faces are processed. This learned skill shows an inversion effect, with upright images being more accurately identified than inverted ones.
Area of Science:
- Cognitive Psychology
- Radiology
- Medical Imaging Analysis
Background:
- Expert perception relies on rapid stimulus detection and categorization.
- Holistic perception, where stimuli are processed as integrated wholes, is theorized to underlie expert rapid detection.
- Radiological expertise may involve holistic processing, analogous to face perception.
Purpose of the Study:
- To investigate whether radiological perception of mammograms exhibits inversion effects, a hallmark of holistic processing.
- To compare the perception abilities of experienced radiologists and radiology residents.
- To determine if holistic processing in mammogram interpretation is a learned skill.
Main Methods:
- Experienced and resident radiologists judged the normality of upright and inverted mammograms.
- Participants also judged upright and inverted facial expressions (happy/neutral) for comparison.
- Accuracy and response times were measured for both tasks.
Main Results:
- Facial expression discrimination was significantly better for upright faces, confirming the expected inversion effect.
- Experienced radiologists showed a similar inversion effect for mammograms, with higher accuracy for upright images.
- Radiology residents performed worse and did not exhibit an inversion effect for mammograms.
Conclusions:
- Mammogram interpretation by experienced radiologists demonstrates characteristics of holistic processing, including an inversion effect.
- The absence of an inversion effect in less experienced residents suggests this is a learned skill.
- Holistic processing contributes to the expertise in rapid mammogram abnormality detection.
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