The psychophysics of texture segmentation
Early vision and beyond
Statistical texture characterization from discrete wavelet representations
IEEE Transactions on Image Processing
Robust clustering of eye movement recordings for quantification of visual interest
Proceedings of the 2004 symposium on Eye tracking research & applications
Visual interest and NPR: an evaluation and manifesto
Proceedings of the 3rd international symposium on Non-photorealistic animation and rendering
Use of eye movements as feedforward training for a synthetic aircraft inspection task
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
ACM Transactions on Applied Perception (TAP)
Improving visual search with image segmentation
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Gaze-augmented think-aloud as an aid to learning
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Proceedings of the 7th Nordic Conference on Human-Computer Interaction: Making Sense Through Design
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The primary detector of breast cancer is the human eye, as it examines mammograms searching for signs of the disease. Nonetheless, it has been shown that 10-30% of all cancers in the breast are not reported by the radiologist, even though most of these are visible retrospectively. Studies of eye position have shown that the eye tends to dwell in the locations of both reported and not reported cancers, indicating that the problem is not faulty visual search, but rather, that is primarily related to perceptual and decision making mechanisms. In this paper we model the areas that attracted the radiologists' visual attention when reading mammograms and that yielded a decision by the radiologist, being this decision overt or covert. We contrast the characteristics of areas that contain cancers that were reported from the ones that contain cancers that, albeit attracting attention, did not reach an internal conspicuity threshold to be reported.