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首页> 外文期刊>Journal of refractive surgery >Estimating visual quality from wavefront aberration measurements.
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Estimating visual quality from wavefront aberration measurements.

机译:通过波前像差测量估算视觉质量。

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PURPOSE: Root mean square (RMS) wavefront error may not be the best metric for predicting a patient's visual function; other metrics should be considered. We describe the most important metrics of optical quality, which are being investigated to predict vision quality and visual performance. METHODS: Optical quality can be described in two different ways. Pupil plane metrics describe variability of the wavefront error at the pupillary plane (eg, RMS wavefront error). Image plane metrics describe the retinal image and do so for either a point source of light (eg, point-spread function [PSF]) or sinusoidal gratings (optical transfer function [OTF]). Visual quality metrics, however, must also consider neural processing and subjective perception. RESULTS: Since vision is more sensitive to rays coming from the center of the pupil, "pupil fraction" appears to be a better predictor of visual acuity (r2 = 0.50) than RMS error (r2 = 0.13). However, image plane metrics, such as the visual Strehl ratio (r2 = 0.62) and the volume between the optical transfer function and neural contrast sensitivity function (r2 = 0.80) appear to be even better. CONCLUSION: Visual perception is highly subjective and involves many aspects of image quality. A single metric to describe all aspects of image quality may be unrealistic. Nevertheless, improved visual quality metrics need further investigation and will likely involve preferential weighing of light passing through the central area of the pupil and/or incorporating neural factors into image quality computation.
机译:目的:均方根(RMS)波前误差可能不是预测患者视觉功能的最佳指标;应该考虑其他指标。我们描述了光学质量的最重要指标,目前正在研究这些指标以预测视觉质量和视觉性能。方法:可以用两种不同的方式描述光学质量。学生平面度量描述了瞳孔平面处波前误差的变化性(例如RMS波前误差)。像平面度量描述视网膜图像,并针对点光源(例如,点扩展函数[PSF])或正弦光栅(光学传递函数[OTF])进行描述。但是,视觉质量指标还必须考虑神经处理和主观感知。结果:由于视觉对来自瞳孔中心的光线更敏感,因此“瞳孔分数”似乎是比RMS误差(r2 = 0.13)更好的视敏度预测指标(r2 = 0.50)。但是,像平面度量,例如视觉Strehl比(r2 = 0.62)以及光学传递函数和神经对比敏感度函数之间的体积(r2 = 0.80)似乎更好。结论:视觉感知是高度主观的,并且涉及图像质量的许多方面。描述图像质量所有方面的单一指标可能是不现实的。然而,改善的视觉质量度量需要进一步研究,并且可能涉及优先权衡通过瞳孔中心区域的光和/或将神经因素纳入图像质量计算中。

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