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Automated Interpretation of Optic Nerve Images: A Data Mining Framework for Glaucoma Diagnostic Support
 

Summary: Automated Interpretation of Optic Nerve Images: A Data Mining Framework for
Glaucoma Diagnostic Support
Syed SR. Abidia
, Paul H. Artesb
, Sanjan Yuna
, ,
Jin Yua
a
NICHE Research Group, Faculty of Computer Science, Dalhousie University, Halifax, Canada
b
Department of Ophthalmology and Visual Sciences, Dalhousie University, Halifax, Canada
Abstract
Confocal Scanning Laser Tomography (CSLT) techniques
capture high-quality images of the optic disc (the retinal re-
gion where the optic nerve exits the eye) that are used in the
diagnosis and monitoring of glaucoma. We present a hybrid
framework, combining image processing and data mining
methods, to support the interpretation of CSLT optic nerve
images. Our framework features (a) Zernike moment methods
to derive shape information from optic disc images; (b) classi-

  

Source: Abidi, Syed Sibte Raza - Faculty of Computer Science, Dalhousie University

 

Collections: Computer Technologies and Information Sciences