Eye Motion Tracking for Medical Image Interpretation Training

Junjian Huang; Junaid Raja; Chanler Cantor; William Marx; Sam Galgano; Jessica Zarzour; Theresa Caridi; Andrew John Gunn; Desiree Morgan; Andrew Smith

doi:10.1067/j.cpradiol.2023.08.013

Eye Motion Tracking for Medical Image Interpretation Training

Curr Probl Diagn Radiol. 2023 Nov-Dec;52(6):474-477. doi: 10.1067/j.cpradiol.2023.08.013. Epub 2023 Aug 26.

Authors

Affiliations

¹ Division of Vascular and Interventional Radiology, Department of Radiology, University of Alabama at Birmingham, Birmingham, AL.
² Division of Vascular and Interventional Radiology, Department of Radiology, University of Alabama at Birmingham, Birmingham, AL. Electronic address: junaid.y.raja@gmail.com.
³ Intuitive Research and Technology, Huntsville, AL.
⁴ Department of Radiology, University of Alabama at Birmingham; Birmingham, AL.

PMID: 37739877
DOI: 10.1067/j.cpradiol.2023.08.013

Abstract

Introduction: The significance of Eye Motion Tracking in aiding learners in training search patterns, pattern recognition, and efficiently using their gaze in terms of time and scanning distribution has been highlighted in the USAF Pilot Training Next initiative.

Methods: The innovation described further builds on this concept in the realm of medical imaging and the provision of real-time feedback of eye direction and gaze duration.

Results: This real-time indicator enables the trainer to adapt verbal queueing of the trainee in a personalized manner to improve knowledge transfer, and to increase the confidence of the trainer and trainee in the competency of the trainee. The initial experiment data set included bone radiographs, digital subtraction angiograms, and computed tomography images.

Discussion: Preliminary results and formative feedback from participants was encouraging with expert viewers able to use Eye Motion Tracking to successfully guide novice readers through search and gaze protocol patterns of the medical images.