Current improvements in interpretation of posterior capsular opacification images

A. Paplinski
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Abstract

We present an application of curvature-driven min/max flow and anisotropic diffusion in processing posterior capsular (PCO) images. PCO images present the back surface of the lens implanted during cataract surgery and are used to monitor the state of the patient's vision. Our standard segmentation technique which is based on the variance based co-occurrence matrices often requires an enhancement of variance images prior to segmentation. A number of enhancement methods are based on partial differential equations, and we present two such methods. We demonstrate that the curvature-driven flow seems to enhance better the significant edges in the image, whereas the anisotropic diffusion seems to work better with smoothing intra-regional image features.
后囊膜混浊图像解释的最新进展
我们提出了曲率驱动的最小/最大流量和各向异性扩散在后囊膜(PCO)图像处理中的应用。PCO图像显示白内障手术中植入的晶状体的背面,用于监测患者的视力状态。我们的标准分割技术是基于方差共现矩阵的,通常需要在分割前对方差图像进行增强。许多增强方法是基于偏微分方程的,我们提出了两种这样的方法。我们证明,曲率驱动的流动似乎可以更好地增强图像中的重要边缘,而各向异性扩散似乎可以更好地平滑区域内的图像特征。
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