Modeling and optimization of closed-loop retinal motion tracking in scanning light ophthalmoscopy

Area of Science:

• Ophthalmology
• Biomedical Engineering
• Optical Imaging

Background:

• Adaptive Optics Scanning Light Ophthalmoscopy (AOSLO) enables high-resolution retinal imaging.
• Accurate retinal motion tracking is crucial for stabilizing AOSLO images.
• Previous systems faced limitations in tracking fidelity and computational efficiency.

Purpose of the Study:

• To develop and optimize a closed-loop retinal motion tracking model for AOSLO.
• To enhance the performance of retinal motion tracking by minimizing residual motion.
• To reduce computational cost while improving tracking accuracy.

Main Methods:

• Built a closed-loop retinal motion tracking model for AOSLO.
• Evaluated retinal motion measurement fidelity and system transfer functions.
• Analyzed power spectral density of human retinal motion.
• Incorporated motion prediction to compensate for scanner retracing periods.

Main Results:

• Optimized control gain and sampling frequency for improved tracking.
• Achieved a 33% improvement in residual image motion performance.
• Reduced computational cost by nearly 50% compared to previous setups.
• Reached a 3 dB bandwidth of 15-17 Hz, approaching the system's frame rate.

Conclusions:

• The optimized closed-loop tracking model significantly enhances AOSLO image stability.
• The system achieves high-fidelity retinal motion tracking with reduced computational demands.
• This advancement facilitates clearer and more reliable in vivo retinal imaging.