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The labeling of large quantities of medical video data by clinicians is a tedious and time consuming task. In addition, the labeling process itself is rigid, since it requires the expert’s interaction to classify image contents into a limited number of predetermined categories. This paper describes an architecture to accelerate the labeling step using eye movement tracking data. We report some initial...
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