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通过数字后照光图像融合在PCO的摄影评估中消除反射。

Removal of reflections in the photographic assessment of PCO by fusion of digital retroillumination images.

作者信息

Findl Oliver, Buehl Wolf, Siegl Hannes, Pinz Axel

机构信息

Department of Ophthalmology, University of Vienna, Währinger Gürtel 18-20, A-1090 Vienna, Austria.

出版信息

Invest Ophthalmol Vis Sci. 2003 Jan;44(1):275-80. doi: 10.1167/iovs.02-0619.

Abstract

PURPOSE

Automated image-analysis systems for objective assessment of posterior capsule opacification (PCO) depend on good image quality. One major drawback is the existence of light-reflection artifacts (Purkinje spots) in retroillumination images of the posterior capsule. Therefore, a software algorithm was developed that removes these artifacts by fusion of two or more digital images from the same eye, photographed in slightly different directions of gaze.

METHODS

The image-fusion process comprises five steps: definition of a primary and a secondary image, automated segmentation of the region of interest and the Purkinje spots, manual selection of three pairs of corresponding points in both images, geometric registration and radiometric calibration of the regions to be inserted from the secondary image into the primary image. The program was tested with an image set of 30 eyes that had various degrees of PCO. A digital image acquisition system with a coaxial optical path was used to take retroillumination images from each eye in at least three different directions of gaze.

RESULTS

In 28 cases all light-reflection artifacts within the capsulorrhexis rim could be removed entirely. In two cases, small parts of single Purkinje spots remained visible, because the reflections were located too closely in the primary and the secondary images.

CONCLUSIONS

Fusion of digital retroillumination images provides high-quality, reflection-free PCO images. This allows objective PCO assessment systems to analyze 100% of the posterior capsule, leading to more accurate results.

摘要

目的

用于客观评估后囊膜混浊(PCO)的自动图像分析系统依赖于良好的图像质量。一个主要缺点是后囊膜的视网膜反光图像中存在光反射伪影(浦肯野斑)。因此,开发了一种软件算法,通过融合来自同一只眼睛、在略微不同注视方向拍摄的两个或更多数字图像来去除这些伪影。

方法

图像融合过程包括五个步骤:定义主图像和副图像、自动分割感兴趣区域和浦肯野斑、在两幅图像中手动选择三对对应点、将副图像中要插入主图像的区域进行几何配准和辐射校准。该程序用一组30只眼睛的图像集进行了测试,这些眼睛具有不同程度的PCO。使用具有同轴光路的数字图像采集系统,从每只眼睛至少在三个不同注视方向拍摄视网膜反光图像。

结果

在28例中,撕囊边缘内的所有光反射伪影均可完全去除。在两例中,单个浦肯野斑的小部分仍可见,因为主图像和副图像中的反射位置过于靠近。

结论

数字视网膜反光图像融合可提供高质量、无反射的PCO图像。这使得客观的PCO评估系统能够分析100%的后囊膜,从而获得更准确的结果。

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