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Head Turn During Visual Field Testing to Minimize the Influence of Prominent Facial Anatomy
Seyedmostafa Sadegh Mousavi1, Sepideh Jamali Dogahe, Lance J Lyons
1Department of Ophthalmology, Mayo Clinic, Rochester, Minnesota.
Summary
Turning the head during visual field testing can significantly expand the testable area. A convolutional neural network (CNN) accurately predicts the optimal head turn angle to maximize peripheral vision.
Area of Science:
- Ophthalmology
- Medical Imaging
- Computer Vision
Background:
- Facial anatomy can limit peripheral visual field, potentially masking defects during standard perimetry.
- Optimizing head position during visual field testing is crucial for accurate assessment.
Purpose of the Study:
- To investigate the effectiveness of head turning during perimetry to maximize the testable visual field.
- To develop and validate a convolutional neural network (CNN) for predicting optimal head turn angles.
Main Methods:
- Six healthy participants underwent visual field testing with the head in primary position, manually turned, and at a CNN-predicted angle.
- A CNN analyzed facial photographs to determine the optimal head turn angle for maximizing visual field exposure.
Main Results:
- A head turn of 15° away from the tested eye (manual) and an average of 12.6° (automated) maximized visual field exposure.
- The mean visual field threshold was significantly higher at the optimal head turn angle compared to the standard position (P=0.02).
Conclusions:
- Head turning during perimetry effectively increases the testable visual field by reducing facial obstruction.
- The developed CNN accurately predicts individual optimal head turn angles for enhanced visual field assessment.
