Automated Insight Tool: Analyzing Eye Tracking Data of Expert and Novice Radiologists During Optic Disc Detection Task
Author:
Affiliation:
1. Department of Computer Science and Engineering, Amrita School of Computing, Bengaluru, Amrita Vishwa Vidyapeetham, India
2. Department of Computer Science, Brunel University London, United Kingdom
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3649902.3656355
Reference23 articles.
1. J Amudha and Neelima Kulkarni. 2016. System and Method for Detection of Features in an Image Using Knowledge of Expert’s Eye Gaze Pattern.
2. R Bhattarai and M Phothisonothai. 2019. Eye-Tracking Based Visualizations and Metrics Analysis for Individual Eye Movement Patterns. In 16th International Joint Conference on Computer Science and Software Engineering (JCSSE). 381–384.
3. Deep Learning based Eye Gaze Tracking for Automotive Applications: An Auto-Keras Approach
4. Budai. 2013. Robust vessel segmentation in fundus images. Int. J. Biomed. Imaging 2013 (Dec. 2013), 154860.
5. The visualisation of eye-tracking scanpaths: what can they tell us about how clinicians view electrocardiograms?
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