pp. 187-201
S&M2803 Research Paper of Special Issue https://doi.org/10.18494/SAM3556 Published: January 27, 2022 Freeform Surface Lens Design Using Genetic Algorithm with Acrylic Material for Reducing Aberrations in Multifocal Artificial Intraocular Lens to Enhance Image Sensing Quality [PDF] Chih-Ta Yen and Shih-Cyuan Jin (Received May 25, 2021; Accepted December 2, 2021) Keywords: intraocular lens (IOL), third-order aberrations, freeform surface lens, genetic algorithm (GA)
A complex intraocular lens (IOL) design involving numerous uncertain variables is proposed. We integrated a genetic algorithm (GA) with a freeform surface lens by using CODE V optical design software to design a multifocal IOL for the human eye. We mainly used a freeform surface lens of acrylic material in the initial crystalline state to enhance image sensing quality; therefore, we used the internal human eye model in the software. The proposed optimization algorithm employs a GA method to optimally simulate the focusing function of the human eye; in this method, the thickness and curvature of the anterior lens and the posterior part of the IOL were varied. We performed a comparison of the proposed GA-designed IOLs and those designed using a CODE V built-in optimization algorithm for the hyperopia 300 degree condition of the human eye. When the pupil entrance was 6 mm, the proposed IOL design improved the RMS of the spot diagram by approximately 11.99 and 10.65% for the human eye to object distances of 35 cm and infinity, respectively. Moreover, the modulation transfer function (MTF) was improved by approximately 5.06 and 15.06% for distances of 35 cm and infinity at a spatial frequency of 15 cycles/mm, respectively.
Corresponding author: Chih-Ta YenThis work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Chih-Ta Yen and Shih-Cyuan Jin, Freeform Surface Lens Design Using Genetic Algorithm with Acrylic Material for Reducing Aberrations in Multifocal Artificial Intraocular Lens to Enhance Image Sensing Quality, Sens. Mater., Vol. 34, No. 1, 2022, p. 187-201. |