Related Experiment Video
Updated: May 1, 2026
Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects
Published on: November 30, 2018
Towards a framework for analysis of eye-tracking studies in the three dimensional environment: a study of visual
E Helbren1, S Halligan, P Phillips
1Centre for Medical Imaging, University College London, London, UK.
Objective:
Eye tracking in three dimensions is novel, but established descriptors derived from two-dimensional (2D) studies are not transferable. We aimed to develop metrics suitable for statistical comparison of eye-tracking data obtained from readers of three-dimensional (3D) "virtual" medical imaging, using CT colonography (CTC) as a typical example.
Methods:
Ten experienced radiologists were eye tracked while observing eight 3D endoluminal CTC videos. Subsequently, we developed metrics that described their visual search patterns based on concepts derived from 2D gaze studies. Statistical methods were developed to allow analysis of the metrics.
Results:
Eye tracking was possible for all readers. Visual dwell on the moving region of interest (ROI) was defined as pursuit of the moving object across multiple frames. Using this concept of pursuit, five categories of metrics were defined that allowed characterization of reader gaze behaviour. These were time to first pursuit, identification and assessment time, pursuit duration, ROI size and pursuit frequency. Additional subcategories allowed us to further characterize visual search between readers in the test population.
Conclusion:
We propose metrics for the characterization of visual search of 3D moving medical images. These metrics can be used to compare readers' visual search patterns and provide a reproducible framework for the analysis of gaze tracking in the 3D environment.
Advances In Knowledge:
This article describes a novel set of metrics that can be used to describe gaze behaviour when eye tracking readers during interpretation of 3D medical images. These metrics build on those established for 2D eye tracking and are applicable to increasingly common 3D medical image displays.
