Visual Search Patterns in 3D Pancreatic Imaging: An Eye Tracking Study

TL;DR

This study explores eye tracking in 3D pancreatic CT imaging to understand radiologists' search strategies, addressing a gap in volumetric image analysis and providing insights into diagnostic navigation behaviors.

Contribution

It introduces a novel taxonomy of eye movements during 3D CT navigation and analyzes radiologists' gaze behavior in volumetric medical imaging.

Findings

Collected eye tracking data from radiologists navigating CT scans.

Aligned gaze data with slice navigation to visualize pancreatic representation.

Analyzed spatial and temporal gaze behavior during diagnosis.

Abstract

Eye tracking has emerged as a powerful tool for examining visual perception and search strategies in various domains, including medicine. While it is relatively straightforward to apply in 2D settings, its use in 3D medical imaging remains challenging and not yet well explored. This gap is particularly relevant for radiology, where volumetric images such as computed tomography (CT) scans are routinely read by medical experts. Radiologists typically interpret these images by navigating through hundreds of 2D slices, most often viewed in the axial projection. A taxonomy of eye movement data during navigation through a CT volume could be valuable to understand how radiologists approach diagnostic tasks. As an example of the derived taxonomy, we asked two radiologists to search abdominal CTs of the pancreas. We collect eye tracking data and align eye gaze movements with slice navigation to visualize the representation of the pancreas through volume and analyze clinicians' gaze behavior in both space and time.