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Proceedings Paper

Individualised training to address variability of radiologists' performance
Author(s): Shanghua Sun; Paul Taylor; Louise Wilkinson; Lisanne Khoo
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Paper Abstract

Computer-based tools are increasingly used for training and the continuing professional development of radiologists. We propose an adaptive training system to support individualised learning in mammography, based on a set of real cases, which are annotated with educational content by experienced breast radiologists. The system has knowledge of the strengths and weakness of each radiologist's performance: each radiologist is assessed to compute a profile showing how they perform on different sets of cases, classified by type of abnormality, breast density, and perceptual difficulty. We also assess variability in cognitive aspects of image perception, classifying errors made by radiologists as errors of search, recognition or decision. This is a novel element in our approach. The profile is used to select cases to present to the radiologist. The intelligent and flexible presentation of these cases distinguishes our system from existing training tools. The training cases are organised and indexed by an ontology we have developed for breast radiologist training, which is consistent with the radiologists' profile. Hence, the training system is able to select appropriate cases to compose an individualised training path, addressing the variability of the radiologists' performance. A substantial part of the system, the ontology has been evaluated on a large number of cases, and the training system is under implementation for further evaluation.

Paper Details

Date Published: 6 March 2008
PDF: 10 pages
Proc. SPIE 6917, Medical Imaging 2008: Image Perception, Observer Performance, and Technology Assessment, 69170G (6 March 2008); doi: 10.1117/12.770296
Show Author Affiliations
Shanghua Sun, Univ. College London (United Kingdom)
Paul Taylor, Univ. College London (United Kingdom)
Louise Wilkinson, St. George's NHS Trust (United Kingdom)
Lisanne Khoo, St. George's NHS Trust (United Kingdom)

Published in SPIE Proceedings Vol. 6917:
Medical Imaging 2008: Image Perception, Observer Performance, and Technology Assessment
Berkman Sahiner; David J. Manning, Editor(s)

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