Claudia Mello-Thoms1. 1. Department of Radiology, University of Pittsburgh, Magee-Women's Hospital, 300 Halket St, Suite 4200, Pittsburgh, PA 15213-3180, USA.
Abstract
RATIONALE AND OBJECTIVE: The author performed this study to determine how image-based elements are translated into decisions by radiologists with different levels of experience in the reading of mammograms. MATERIALS AND METHODS: Three full-time mammographers and four radiology residents read 40 two-view mammogram cases. The observers' eye position was tracked while they searched the mammograms for malignancies. Spatial frequency analysis was performed to relate what the observers reported with where they looked. RESULTS: Statistically significant differences were found between lesion-containing areas that attracted visual attention and were correctly interpreted and those that were visually inspected but not reported. In addition, an artificial neural network was successfully trained to map the image characteristics in the visually selected areas on a mammogram and to linkthem to a likely decision by the observer. CONCLUSION: Spatial frequency analysis can be used to derive trends for how mammographers and radiology residents will respond to mammograms.
RATIONALE AND OBJECTIVE: The author performed this study to determine how image-based elements are translated into decisions by radiologists with different levels of experience in the reading of mammograms. MATERIALS AND METHODS: Three full-time mammographers and four radiology residents read 40 two-view mammogram cases. The observers' eye position was tracked while they searched the mammograms for malignancies. Spatial frequency analysis was performed to relate what the observers reported with where they looked. RESULTS: Statistically significant differences were found between lesion-containing areas that attracted visual attention and were correctly interpreted and those that were visually inspected but not reported. In addition, an artificial neural network was successfully trained to map the image characteristics in the visually selected areas on a mammogram and to linkthem to a likely decision by the observer. CONCLUSION: Spatial frequency analysis can be used to derive trends for how mammographers and radiology residents will respond to mammograms.