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12 April 2002 Relating image-based features to mammogram interpretation
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Abstract
Mammography is a widely used technique to screen for breast cancer. However, due to the complexity of the breast tissue and to the low prevalence of cancer in the screening population, between 10-30% of retrospectively visible cancers are not reported. Faulty visual search, that is, not examining the area where the cancer is located, is responsible for a third of these misses, but all other unreported cancers attract some amount of visual attention, as indicated by the duration of visual gaze in the location of the lesion. Thus, perceptual and decision making mechanisms must be understood, in order to aid radiologists to detect cancer at earlier stages. We have been working on modeling these mechanisms by using spatial frequency analysis, in a process that is inspired by the rules and complexity of the eye-brain system. In this paper we analyze the different decision outcomes of experienced mammographers and less experienced radiology residents, undergoing a mammography rotation, when examining a case set of 40 two-view mammogram cases. We also characterize the interplay between local factors, which are related to the area of the image that attracts visual attention, and global factors, which are related to breast sampling, as they affect decision outcome for each group.
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Claudia Mello-Thoms, Calvin F. Nodine, and Harold L. Kundel "Relating image-based features to mammogram interpretation", Proc. SPIE 4686, Medical Imaging 2002: Image Perception, Observer Performance, and Technology Assessment, (12 April 2002); https://doi.org/10.1117/12.462664
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