Assessing Viewing Pattern Consistency in Mammogram Readers
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Date
2009
Authors
Maeder, Anthony
Fookes, C
Journal Title
Journal ISSN
Volume Title
Publisher
Australian Computer Society
Rights
Copyright © 2009, Australian Computer Society, Inc.
Rights Holder
Australian Computer Society, Inc.
Abstract
Breast cancer screening programs typically require very large volumes of x-ray images (mammograms) to be viewed by highly experienced human readers. The readers can recognise a wide range of different visible features indicative of clinically abnormal situations, which they use as a basis to generate a report on their findings. Errors in reporting can occur if the readers fail to identify a particular feature of interest for further visual inspection during the viewing process. This risk is typically reduced by training readers to follow a particular viewing path through an image, which they should be able to apply consistently. Knowledge of the extent of consistency in this viewing behaviour within and between viewers would inform the development of an automated checking approach, based on monitoring of viewer visual attention. This paper presents an analysis of some reader viewing pattern profiles obtained using eye tracking with an infra red computer vision system, as a basis for developing a suitable consistency assessment model. .
Description
This paper appeared at the Australasian Workshop on Health Informatics and Knowledge Management (HIKM 2009), Wellington, New Zealand. Conferences in Research and Practice in Information Technology (CRPIT), Vol. 97. J. Warren, Ed. Reproduction for academic, not-for profit purposes permitted provided this text is included.
Keywords
medical image, eye tracking, visual attention, Mammogram
Citation
Maeder, A.J. and Fookes, C. (2009). Assessing viewing pattern consistency in mammogram readers. In Proceedings of the Third Australasian Workshop on Health Informatics and Knowledge Management. Darlinghurst NSW: Australian Computer Society. Proceedings of the Third Australasian Workshop on Health Informatics and Knowledge Management. Wellington, New Zealand. Jan 2009, pp. 7-12.