Publication Type : Conference Paper
Publisher : ACM
Source : Proceedings of the 2024 Symposium on Eye Tracking Research and Applications
Url : https://doi.org/10.1145/3649902.3656355
Campus : Bengaluru
School : School of Computing
Year : 2024
Abstract : In specialized medical research, eye-tracking analysis proves instrumental for monitoring and dissecting eye movements and gaze patterns. This methodology is employed to get insights into diverse human behavior, cognition, and health facets. This study analyzes radiologists gaze patterns as they locate optic discs in retinal fundus images. The underlying premise is that experts possess a more profound understanding of the designated area of interest (AOI) within retinal images than non-experts. We considered visual attention distribution, and the visual focus shift between experts and novice during the viewing task. Identifying expert radiologists will benefit in two main ways: first, it will facilitate the development of an effective training system that assists radiologists in recognizing their technical proficiency, and second, it will enable the automation of the diagnostic process. The proposed methodology utilizes insights from radiologists Region of Interest (IOR) to interpret experts and novice eye gaze behavior, classify radiologists expertise levels, and compare visual patterns among different expertise levels. This study introduces an automated tool to analyze experts behaviors within regions of interest, offering a comprehensive understanding of radiological diagnostic processes.
Cite this Research Publication : Aiswariya Milan K, Amudha J, George Ghinea, Automated Insight Tool: Analyzing Eye Tracking Data of Expert and Novice Radiologists During Optic Disc Detection Task, Proceedings of the 2024 Symposium on Eye Tracking Research and Applications, ACM, 2024, https://doi.org/10.1145/3649902.3656355