Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, Ilmenau, Germany.
Department of General Health Studies, Karl Landsteiner University of Health Science, Krems, Austria.
Transl Vis Sci Technol. 2023 Jul 3;12(7):21. doi: 10.1167/tvst.12.7.21.
Morphological changes to the optic nerve head (ONH) can be detected at the early stages of glaucoma. Three-dimensional imaging and analysis may aid in the diagnosis. Light field (LF) fundus cameras can generate three-dimensional (3D) images of optic disc topography from a single shot and are less susceptible to motion artifacts. Here, we introduce a processing method to determine diagnostically relevant ONH parameters automatically and present the results of a subject study performed to validate this method.
The ONHs of 17 healthy subjects were examined and images were acquired with both an LF fundus camera and by optical coherence tomography (OCT). The LF data were analyzed with a novel algorithm and compared with the results of the OCT study. Depth information was reconstructed, and a model with radial basis functions was used for processing of the 3D point cloud and to provide a finite surface. The peripapillary rising and falling edges were evaluated to determine optic disc and cup contours and finally calculate the parameters.
Nine of the 17 subjects exhibited prominent optic cups. The contours and ONH parameters determined by an analysis of LF 3D imaging largely agreed with the data obtained from OCT. The median disc areas, cup areas, and cup depths differed by 0.17 mm², -0.04 mm², and -0.07 mm, respectively.
The findings presented here suggest the possibility of using LF data to evaluate the ONH.
LF data can be used to determine geometric parameters of the ONH and thus may be suitable for future use in glaucoma diagnostics.
视神经头(ONH)的形态变化可以在青光眼的早期阶段检测到。三维成像和分析可能有助于诊断。光场(LF)眼底相机可以从单次拍摄中生成视盘 topography 的三维(3D)图像,并且不易受到运动伪影的影响。在这里,我们介绍了一种处理方法,可以自动确定诊断相关的 ONH 参数,并介绍了一项为验证该方法而进行的受试者研究的结果。
对 17 名健康受试者的 ONH 进行了检查,并使用 LF 眼底相机和光学相干断层扫描(OCT)采集了图像。使用一种新的算法对 LF 数据进行了分析,并与 OCT 研究的结果进行了比较。重建了深度信息,并使用径向基函数模型对 3D 点云进行了处理,并提供了有限的表面。评估了视盘周围的上升和下降边缘,以确定视盘和杯状轮廓,并最终计算出参数。
17 名受试者中有 9 名表现出明显的杯状。通过 LF 3D 成像分析确定的轮廓和 ONH 参数与从 OCT 获得的数据基本一致。盘面积、杯面积和杯深度的中位数分别相差 0.17 mm²、-0.04 mm² 和-0.07 mm。
这里提出的结果表明,使用 LF 数据评估 ONH 的可能性。
刘晓燕