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Analyzing Sub-Classifications of Glaucoma via SOM Based Clustering of Optic Nerve Images
Sanjun Yan, Syed Sibte Raza Abidi, Paul Habib Artes
483 - 488
Studies in Health Technology and Informatics
Volume 116: Connecting Medical Informatics and Bio-Informatics
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 obtained from glaucoma patients and healthy controls.

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