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Summary: Analyzing Sub-Classifications of Glaucoma
via SOM Based Clustering of Optic Nerve
Images
Sanjun Yan
a
, Syed Sibte Raza Abidi
a
, Paul Habib Artes
b
a
Health Informatics Lab, Faculty of Computer Science, Dalhousie University, Halifax, Canada
b
Department of Ophthalmology and Visual Sciences, Dalhousie University, Halifax, Canada
Abstract
We present a data mining framework to cluster optic nerve images obtained by Confocal
Scanning Laser Tomography (CSLT) in normal subjects and patients with glaucoma.
We use self-organizing maps and expectation maximization methods to partition the
data into clusters that provide insights into potential sub-classification of glaucoma
based on morphological features. We conclude that our approach provides a first step
towards a better understanding of morphological features in optic nerve images
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