Bayesian model of Snellen visual acuity
Bayesian model of Snellen visual acuity
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DOI：
10.1364/josaa.20.001371
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发表时间：
2003-07-01
影响因子：
1.9
通讯作者：
Antona, B
中科院分区：
文献类型：
--
作者：
Nestares, O;Navarro, R;Antona, B
Snellen视敏度（VA）的贝叶斯模型已经开发出来，据我们所知，是第一个包括VA的三个主要阶段：（1）光学退化，（2）神经图像表示和对比度阈值，（3）字符识别。从实验波像差数据中获得了Snellen测试图的视网膜图像。然后，将具有一组调整到不同空间频率和方向的视觉通道的子带图像分解应用于视网膜图像，就像早期皮质图像表示的标准计算模型一样。将神经阈值应用于对比度响应以包括神经对比敏感度的影响。由此产生的图像表示是贝叶斯模式识别方法的基础，该方法对光学像差的存在具有鲁棒性。该模型被应用到图像包含在不同尺度的字母视标集，并在每个尺度上获得正确答案的数量，最终输出是十进制斯内伦VA。该模型没有可供调整的自由参数。主要输入数据是眼睛的光学像差，并且当没有对象特定值可用时，标准值用于所有其他参数，包括Stiles-Crawford效应、视觉通道和神经对比度阈值。当像差较大时，涉及图案识别的Snellen VA不同于光栅敏锐度，光栅敏锐度基于更简单的检测（或取向辨别）任务，因此基本上不受光学传递函数引入的相位失真的影响。在一个主题的模型的初步测试产生的实际测量值和预测VA值之间的密切协议。还包括两个例子：（1）应用该方法预测屈光手术患者的VA和（2）通过矫正眼像差可获得的VA的模拟。(C)2003年美国光学学会。
A Bayesian model of Snellen visual acuity (VA) has been developed that, as far as we know, is the first one that includes the three main stages of VA: (1) optical degradations, (2) neural image representation and contrast thresholding, and (3) character recognition. The retinal image of a Snellen test chart is obtained from experimental wave-aberration data. Then a subband image decomposition with a set of visual channels tuned to different spatial frequencies and orientations is applied to the retinal image, as in standard computational models of early cortical image representation. A neural threshold is applied to the contrast responses to include the effect of the neural contrast sensitivity. The resulting image representation is the base of a Bayesian pattern-recognition method robust to the presence of optical aberrations. The model is applied to images containing sets of letter optotypes at different scales, and the number of correct answers is obtained at each scale; the final output is the decimal Snellen VA. The model has no free parameters to adjust. The main input data are the eye's optical aberrations, and standard values are used for all other parameters, including the Stiles-Crawford effect, visual channels, and neural contrast threshold, when no subject specific values are available. When aberrations are large, Snellen VA involving pattern recognition differs from grating acuity, which is based on a simpler detection (or orientation-discrimination) task and hence is basically unaffected by phase distortions introduced by the optical transfer function. A preliminary test of the model in one subject produced close agreement between actual measurements and predicted VA values. Two examples are also included: (1) application of the method to the prediction of the VA in refractive-surgery patients and (2) simulation of the VA attainable by correcting ocular aberrations. (C) 2003 Optical Society of America.