School of Optometry, Indiana University, Bloomington, USA.
Ophthalmic Physiol Opt. 2014 Jan;34(1):63-72. doi: 10.1111/opo.12097. Epub 2013 Oct 31.
Conventional aberration analysis by a Shack-Hartmann aberrometer is based on the implicit assumption that an injected probe beam reflects from a single fundus layer. In fact, the biological fundus is a thick reflector and therefore conventional analysis may produce errors of unknown magnitude. We developed a novel computational method to investigate this potential failure of conventional analysis.
The Shack-Hartmann wavefront sensor was simulated by computer software and used to recover by two methods the known wavefront aberrations expected from a population of normally-aberrated human eyes and bi-layer fundus reflection. The conventional method determines the centroid of each spot in the SH data image, from which wavefront slopes are computed for least-squares fitting with derivatives of Zernike polynomials. The novel 'global' method iteratively adjusted the aberration coefficients derived from conventional centroid analysis until the SH image, when treated as a unitary picture, optimally matched the original data image.
Both methods recovered higher order aberrations accurately and precisely, but only the global algorithm correctly recovered the defocus coefficients associated with each layer of fundus reflection. The global algorithm accurately recovered Zernike coefficients for mean defocus and bi-layer separation with maximum error <0.1%. The global algorithm was robust for bi-layer separation up to 2 dioptres for a typical SH wavefront sensor design. For 100 randomly generated test wavefronts with 0.7 D axial separation, the retrieved mean axial separation was 0.70 D with standard deviations (S.D.) of 0.002 D.
Sufficient information is contained in SH data images to measure the dioptric thickness of dual-layer fundus reflection. The global algorithm is superior since it successfully recovered the focus value associated with both fundus layers even when their separation was too small to produce clearly separated spots, while the conventional analysis misrepresents the defocus component of the wavefront aberration as the mean defocus for the two reflectors. Our novel global algorithm is a promising method for SH data image analysis in clinical and visual optics research for human and animal eyes.
传统的夏克-哈特曼像差仪的像差分析基于一个隐含的假设,即注入的探测光束仅从一个眼底层反射。事实上,生物眼底是一个厚反射器,因此传统分析可能会产生未知大小的误差。我们开发了一种新的计算方法来研究这种传统分析可能出现的失败。
通过计算机软件模拟夏克-哈特曼波前传感器,并使用两种方法从正常像差的人群眼中的已知波前像差和双层眼底反射中恢复。传统方法确定 SH 数据图像中每个光斑的质心,从该质心计算波前斜率,通过对泽尼克多项式的导数进行最小二乘拟合。新的“全局”方法迭代调整由传统质心分析得出的像差系数,直到 SH 图像被视为一个整体图像,从而最佳地匹配原始数据图像。
两种方法都能准确、精确地恢复高阶像差,但只有全局算法能正确恢复与眼底反射各层相关的离焦系数。全局算法准确地恢复了平均离焦和双层分离的泽尼克系数,最大误差<0.1%。对于典型的 SH 波前传感器设计,全局算法在双层分离高达 2 屈光度时仍具有鲁棒性。对于 100 个随机生成的测试波前,轴向分离为 0.7 D,所得到的平均轴向分离为 0.70 D,标准偏差(S.D.)为 0.002 D。
SH 数据图像中包含足够的信息来测量双层眼底反射的屈光厚度。全局算法是优越的,因为它成功地恢复了与两个眼底层相关的焦点值,即使它们的分离小到无法产生明显分离的光斑,而传统分析则错误地将波前像差的离焦分量表示为两个反射器的平均离焦。我们的新全局算法是用于人类和动物眼睛的临床和视觉光学研究中 SH 数据图像分析的一种很有前途的方法。