Studying visual behaviors from multiple eye tracking features across levels of information representation

While eye movements have been used to analyze behaviors for many years, research studies that employ eye tracking technologies are often limited to basic physical features and fixations, which leads to an abundance of data. Because visual behaviors are complex in nature, it can be difficult to make comparisons and conclusions based on subjects' scanpaths. In this study, we analyze visual activities from 15 expert radiographers and 26 novices as they view a series of images to attempt to discover relationships between a large number of features including fixation, region and subject information. We expect that the techniques used in this study will be useful in finding common behaviors in eye tracking data for medical applications. These behaviors could be used to train novices and prevent potential medical errors that occur during visual analysis of medical images.