Sunday 27 February Speakers

L. Ferreira, J. Furtado, Jason Charng, M. Franchina, A. Molan, Michael, Hunter, D. Mackey, Shi-bang Ma, M. Wilsher, Noor Ali, J. Sims, O. Tomkins-Netzer, Sue, Lightman
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Abstract

8:30am 9:00am L03 – REFRACTIVE UPDATE LECTURE Chair: Dr Jacqueline Beltz Venue: Great Hall 1 & 2 Title: Artificial Intelligence: Applications for Pathologies of the Anterior Segment of the Eye Dr Damien Gatinel Synopsis: The use of artificial intelligence (AI) provides a better understanding of data collected through biometric and imaging techniques. It can increase the accuracy or the effectiveness of solutions intended to correct certain optical defects of the eye caused by structural alterations responsible for a reduction in the transparency of the ocular media and/or refractive errors. This work has been mainly applied to the study of corneal topography and imaging, description of the ocular wavefront, ocular biometry and improving the accuracy of the power calculation of intraocular lenses. We used AI techniques to carry out studies to characterise the alterations observed during the evolution of keratoconus, as well as the spatial distribution of corneal oedema through the use of neural networks to tomographic image analysis. Using artificial intelligence and the results from the description of the ocular wavefront on a new basis, we were able to estimate the real impact of high degree aberrations on subjective refraction. From a thick lens paraxial eye model, we established an analytical formula to calculate the position of the principal planes of an implant based on its geometry and the main biometric constants. This work made it possible to train an algorithm to predict the effective position of an implant, taking into account its geometry and establishing an original biometric calculation formula combining principles of paraxial optics and artificial intelligence algorithms applied to an eye model made up of thick lenses.
2月27日星期日演讲人
上午8:30 - L03 -屈光更新讲座主持人:Jacqueline Beltz博士地点:1号和2号大厅题目:人工智能:眼前段病理的应用Damien Gatinel博士简介:人工智能(AI)的使用使人们更好地理解通过生物识别和成像技术收集的数据。它可以提高解决方案的准确性或有效性,旨在纠正某些由眼部介质透明度降低和/或屈光不正引起的眼睛光学缺陷的结构改变。这项工作主要应用于角膜地形图与成像的研究、眼波前的描述、眼生物测量以及提高人工晶状体度数计算的准确性。我们使用人工智能技术进行研究,通过使用神经网络进行断层图像分析,描述圆锥角膜进化过程中观察到的变化,以及角膜水肿的空间分布。在新的基础上,利用人工智能和眼波前描述的结果,我们能够估计高阶像差对主观折射的实际影响。从一个厚晶状体近轴眼模型出发,我们建立了一个基于植入体几何形状和主要生物特征常数计算植入体主平面位置的解析公式。这项工作可以训练一种算法来预测植入物的有效位置,考虑到它的几何形状,并建立一个原始的生物识别计算公式,结合近轴光学原理和应用于厚透镜组成的眼睛模型的人工智能算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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