Share Email Print

Optical Engineering

Segmentation of a class of ophthalmological images using a directional variance operator and co-occurrence arrays
Author(s): Andrew P. Paplinski; James Frederick Boyce
Format Member Price Non-Member Price
PDF $20.00 $25.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

The posterior capsule opacification images considered are images of the membrane encapsulating an artificial lens implanted during cataract surgery in place of the natural lens. The images are taken to monitor the state of the patient’s vision after the surgery. Subsequent to the surgery, the membrane of the posterior capsule may become opacified, thus degrading the patient’s vision. We discuss the methodology used and the results obtained in the segmentation of the images into transparent and opacified regions. The opacification is primarily characterized by its texture, therefore a directional standard deviation operator is applied to an image giving rise to a family of ‘‘conjugate’’ images. From these images, the multi-dimensional histogram (co-occurrence) array is calculated and subsequently approximated by Gaussian distributions to form the basis for the segmentation step.

Paper Details

Date Published: 1 November 1997
PDF: 8 pages
Opt. Eng. 36(11) doi: 10.1117/1.601552
Published in: Optical Engineering Volume 36, Issue 11
Show Author Affiliations
Andrew P. Paplinski, Monash Univ. (Australia)
James Frederick Boyce, King's College London (United Kingdom)

© SPIE. Terms of Use
Back to Top