The Detection of Opacification on the Posterior Capsule by
London University (September, 1995)
Department of Physics, Wheatstone Laboratory, King's College London, Strand, London WC2R 2LS
As part of a study on the cataracts eye disorder
investigations on how to automatically quantify
the extent of the associated opacification were carried out.
Some 169 digital images of the eyes of patient's
fitted with an artificial lens were systematically
Observations made of these images led to the identification
of four distinct textural region classes.
From an analysis of the differences in textural
properties of these region classes a set of
feature extractors were proposed and validated experimentally.
A feature vector extractor algorithm was developed that
from a set of example sub-image region classes generated
a set of patterns in 4D feature space.
The patterns were then classified with a multi-layer
perceptron back propagation neural network.
Preliminary results on data not used in training indicated
a 100 percent classification accuracy for 800 pixels
extracted from clear regions and a 99 percent classification
accuracy for 800 pixels extracted from opacified ones.
Dissertation in pdf format
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