In:
Klinische Monatsblätter für Augenheilkunde, Georg Thieme Verlag KG, Vol. 239, No. 12 ( 2022-12), p. 1440-1446
Abstract:
Background For quantitative and qualitative evaluation of the imaging properties of IOLs, axial cross-sectional images can be obtained from the 3-dimensional light distribution by
means of an optical bench, as is known from light sheet recordings in fluorescein baths. This paper presents a new image-processing algorithm to enhance the quality of generated axial cross-sectional images, and the two methods are then compared. Material and Methods The 3-dimensional point spread function of a diffractive trifocal IOL (AT LISA tri 839MP, Carl Zeiss Meditec AG, Jena, Germany) was recorded on an optical bench
developed in Rostock for different pupil diameters. A specially adapted image processing algorithm was then applied to the measurements, allowing through-focus curves to be generated. In addition, cross-sectional images of the IOLs studied were acquired using the light sheet method in a fluorescein bath. Results The study clearly shows the superiority of the newly developed method over the light sheet method in terms of image quality. In addition to the individual focal points, fine
focal structures as well as halos can be made visible in the cross-sectional images obtained using the new method. In the generated through-focus curves, 3 intensity peaks can be identified, which represent the near, intermediate and far focus of the tested MIOL and cannot be represented by light sheet methods. Conclusion The interaction of the optical bench with the developed image processing algorithm allows a more detailed understanding of the image formation and false light phenomena of
IOLs, which was restricted by the technical limitations of the existing light sheet method. In addition, other quantities such as the through-focus curve can be derived quantitatively.
Type of Medium:
Online Resource
ISSN:
0023-2165
,
1439-3999
Language:
German
Publisher:
Georg Thieme Verlag KG
Publication Date:
2022
detail.hit.zdb_id:
2039754-9
