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Simultaneous Measurement of Peripheral Ocular Aberrations Using a Virtual Multi-Eccentric Hartmann-Shack Aberrometer
Jennyfer Morales-Marín1, Andrés Osorno-Quiroz2, Walter Torres-Sepúlveda2
1Grupo de Óptica y Fotónica, Instituto de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Antioquia UdeA, Calle 70 No. 52-21, Medellín 050010, Colombia.
A novel virtual multi-eccentric Hartmann-Shack (HS) aberrometer uses a convolutional neural network (CNN) to accurately measure peripheral ocular aberrations. This AI-driven approach overcomes limitations of traditional methods, improving measurement speed and reliability.
Area of Science:
- Ophthalmology
- Computational Optics
- Artificial Intelligence in Vision Science
Background:
- Peripheral ocular aberrations impact vision and are implicated in ametropias.
- Current aberrometry methods often require sequential measurements, increasing time and variability.
- A need exists for rapid, accurate assessment of peripheral vision metrics.
Purpose of the Study:
- To present a computational proof of concept for a virtual multi-eccentric Hartmann-Shack (HS) aberrometer.
- To evaluate the system's performance under ideal and realistic conditions, including image noise.
- To compare a novel convolutional neural network (CNN) approach with traditional methods for aberration quantification.
Main Methods:
- Simulated a virtual multi-eccentric HS aberrometer capturing nine wavefronts within 20° of the fovea.
- Introduced speckle and illumination variations to simulate realistic imaging conditions.
- Quantified aberrations using a traditional centroid-based method and a custom-trained ResNet CNN.
Main Results:
- Speckle significantly degraded traditional aberration reconstructions at eccentric points.
- The CNN, trained on speckled data, demonstrated superior robustness and accuracy across all measured wavefronts.
- The virtual system successfully simulated simultaneous, multi-point wavefront acquisition.
Conclusions:
- A CNN-based approach offers a robust and accurate method for analyzing peripheral ocular aberrations from HS images.
- The proof-of-concept supports the development of a physical multi-eccentric aberrometer for faster, more reliable eye measurements.
- This technology holds promise for ocular treatment evaluation and longitudinal ametropia studies.
