Scientific reports · 2025
Reconstruction of three-dimensional retinal shape from refractive topography data.
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Ma Zhaodi, Fang Lihua, Ma Chongchong, Liu Yutong, Guo Zhuang, Wang Yan
Аннотация
UNLABELLED: A three-dimensional retinal shape was reconstructed by refractive topography (RT).
METHODS: The personalized optical models of the human eye were reconstructed based on geometric parameters from clinical measurements. The expected refraction distribution on the fundus was calculated for each model. Subsequently, the refraction-position conversion function (RPF) was derived by fitting the data sets, which included the field of view (FOV), vitreous thickness (VT), and refraction. Additionally, the coordinates on the fundus of the human eye were calculated from RT data through the RPF. Ultimately, a three-dimensional retinal shape was reconstructed.
RESULTS: The expected refraction was calculated on 6 subjects. The results demonstrate that the expected refraction decreased as the VT increased. However, when the FOV was greater than 8°, the expected refraction increased with increasing FOV. A polynomial was applied to fit the 656 data points, resulting in the formation of the RPF. The fitting results demonstrated that the relationship tended to be similar in general for different human eyes, but there were individual differences. This reconstructed method provided good agreement between the reconstructed three-dimensional retina shape and the OCT measurements.
CONCLUSION: The reconstructed three-dimensional retinal shape from RT data enables new imaging protocols that improve visualization of retinal shape.
METHODS: The personalized optical models of the human eye were reconstructed based on geometric parameters from clinical measurements. The expected refraction distribution on the fundus was calculated for each model. Subsequently, the refraction-position conversion function (RPF) was derived by fitting the data sets, which included the field of view (FOV), vitreous thickness (VT), and refraction. Additionally, the coordinates on the fundus of the human eye were calculated from RT data through the RPF. Ultimately, a three-dimensional retinal shape was reconstructed.
RESULTS: The expected refraction was calculated on 6 subjects. The results demonstrate that the expected refraction decreased as the VT increased. However, when the FOV was greater than 8°, the expected refraction increased with increasing FOV. A polynomial was applied to fit the 656 data points, resulting in the formation of the RPF. The fitting results demonstrated that the relationship tended to be similar in general for different human eyes, but there were individual differences. This reconstructed method provided good agreement between the reconstructed three-dimensional retina shape and the OCT measurements.
CONCLUSION: The reconstructed three-dimensional retinal shape from RT data enables new imaging protocols that improve visualization of retinal shape.