泽尼克多项式
波前
眼睛畸变
视力
彗差(光学)
自适应光学
光学
球差
散光
物理
波前传感器
变形镜
角膜地形图
中央凹
验光服务
眼科
计算机科学
医学
镜头(地质)
视网膜
作者
Karolinne Maia Rocha,Laurent Vabre,Fabrice Harms,Nicolas Château,Ronald R. Krueger
出处
期刊:Journal of Refractive Surgery
[SLACK, Inc.]
日期:2007-11-01
卷期号:23 (9): 953-959
被引量:75
标识
DOI:10.3928/1081-597x-20071101-17
摘要
ABSTRACT PURPOSE: This study measured the changes in visual acuity induced by individual Zernike ocular aberrations of various root-mean-square (RMS) magnitudes. METHODS: A crxl Adaptive Optics Visual Simulator (Imagine Eyes) was used to modify the wavefront aberrations in nine eyes. After measuring ocular aberrations, the device was programmed to compensate for the eye's wavefront error up to the 4th order and successively apply different individual Zernike aberrations using a 5-mm pupil. The generated aberrations included defocus, astigmatism, coma, trefoil, and spherical aberration at a level of 0.1, 0.3, and 0.9 µm. Monocular visual acuity was assessed using computer-generated Lando It-C optotypes. RESULTS: Correction of the patients' aberrations improved visual acuity by a mean of 1 line (-0.1 logMAR) compared to best sphero-cylinder correction. Aberrations of 0.1 µm RMS resulted in a limited decrease in visual acuity (mean +0.05 logMAR), whereas aberrations of 0.3 µm RMS induced significant visual acuity losses with a mean reduction of 1.5 lines (+0.15 logMAR). Larger aberrations of 0.9 µm RMS resulted in greater visual acuity losses that were more pronounced with spherical aberration (+0.64 logMAR) and defocus (+0.62 logMAR), whereas trefoil (+0.22 logMAR) was found to be better tolerated. CONCLUSIONS: The electromagnetic adaptive optics visual simulator effectively corrected and generated wavefront aberrations up to the 4th order. Custom wavefront correction significantly improved visual acuity compared to best-spectacle correction. Symmetric aberrations (eg, defocus and spherical aberration) were more detrimental to visual performance. [J Refract Surg. 2007;23:953-959.]
科研通智能强力驱动
Strongly Powered by AbleSci AI