Journal article
The Perception of Breast Cancer: What Differentiates Missed from Reported Cancers in Mammography?
Academic radiology, Vol.9(9), pp.1004-1012
2002
DOI: 10.1016/S1076-6332(03)80475-0
PMID: 12238541
Abstract
Mammographers map endogenous and exogenous factors into decisions whether to report the presence of a malignant finding in a mammogram case. Thus, to understand how image-based elements are translated into observer-based decisions, the authors used spatial frequency analysis to model the areas on mammograms that attracted visual attention, in addition to the areas localized as abnormal.
Four mammographers read 40 two-view mammogram cases, of which 30 contained at least one malignant lesion visible on one or two views. Their eye positions were recorded during visual search. Once the mammographer felt confident enough to provide an initial impression of the case (“normal” or “abnormal”), the eye position monitoring was turned off and the mammographer indicated, with a mouse-controlled cursor, the location and nature of any malignant findings. Regions that elicited an overt or a covert response by the mammographers were extracted for processing by means of wavelet packets and artificial neural networks.
Different decision outcomes yielded different energy representations, in the spatial frequency domain. These energy representations were used by an artificial neural network to predict decision outcome in areas of interest, derived from eye position analysis, on mammograms from new cases. Individual trends were observed for each mammographer.
Spatial frequency representation of regions that attracted a given mammographer's visual attention may be useful for characterizing how that mammographer will respond to the visually selected areas.
Details
- Title: Subtitle
- The Perception of Breast Cancer: What Differentiates Missed from Reported Cancers in Mammography?
- Creators
- Claudia Mello-Thoms - Department of Radiology, University of Pittsburgh and Magee-Women's Hospital, 300 Halket St, Ste 4200, Pittsburgh, PA, USA 15213-3180Stanley Dunn - Department of Biomedical Engineering, Rutgers University, Piscataway, NJ, USACalvin F Nodine - Department of Radiology, University of Pennsylvania, Philadelphia, USAHarold L Kundel - Department of Radiology, University of Pennsylvania, Philadelphia, USASusan P Weinstein - Department of Radiology, University of Pennsylvania, Philadelphia, USA
- Resource Type
- Journal article
- Publication Details
- Academic radiology, Vol.9(9), pp.1004-1012
- Publisher
- Elsevier Inc
- DOI
- 10.1016/S1076-6332(03)80475-0
- PMID
- 12238541
- ISSN
- 1076-6332
- eISSN
- 1878-4046
- Language
- English
- Date published
- 2002
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology
- Record Identifier
- 9984051745902771
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