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Proceedings Paper

Improvements in interpretation of posterior capsular opacification (PCO) images
Author(s): Andrew P. Paplinski; James Frederick Boyce; Sarah A. Barman
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Paper Abstract

We present further improvements to the methods of interpretation of the Posterior Capsular Opacification (PCO) images. These retro-illumination images of the back surface of the implanted lens are used to monitor the state of patient's vision after cataract operation. A common post-surgical complication is opacification of the posterior eye capsule caused by the growth of epithelial cells across the back surface of the capsule. Interpretation of the PCO images is based on their segmentation into transparent image areas and opaque areas, which are affected by the growth of epithelial cells and can be characterized by the increase in the image local variance. This assumption is valid in majority of cases. However, for different materials used for the implanted lenses it sometimes happens that the epithelial cells grow in a way characterized by low variance. In such a case segmentation gives a relatively big error. We describe an application of an anisotropic diffusion equation in a non-linear pre-processing of PCO images. The algorithm preserves the high-variance areas of PCO images and performs a low-pass filtering of small low- variance features. The algorithm maintains a mean value of the variance and guarantees existence of a stable solution and improves segmentation of the PCO images.

Paper Details

Date Published: 6 June 2000
PDF: 8 pages
Proc. SPIE 3979, Medical Imaging 2000: Image Processing, (6 June 2000); doi: 10.1117/12.387598
Show Author Affiliations
Andrew P. Paplinski, Monash Univ. (Australia)
James Frederick Boyce, King's College London (United Kingdom)
Sarah A. Barman, King's College London (United Kingdom)


Published in SPIE Proceedings Vol. 3979:
Medical Imaging 2000: Image Processing
Kenneth M. Hanson, Editor(s)

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