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CBMS
2005
IEEE

Automated Optic Nerve Analysis for Diagnostic Support in Glaucoma

14 years 5 months ago
Automated Optic Nerve Analysis for Diagnostic Support in Glaucoma
The availability of modern imaging techniques such as Confocal Scanning Laser Tomography (CSLT) for capturing high-quality optic nerve images offer the potential for developing automatic and objective methods for supporting clinical decision-making in glaucoma. We present a hybrid approach that features the analysis of CSLT images using ethods to derive abstract image defining features, and the use of these features to train classifiers for automatically distinguishing CSLT images of healthy and diseased optic nerves. As a first step, in this paper, we present investigations in feature subset selection methods for reducing the relatively large input space produced by the moment methods. Our results demonstrate that our methods discriminate between healthy and glaucomatous optic nerves based on shape information automatically derived from CSLT tomography images.
Jin Yu, Syed Sibte Raza Abidi, Paul Habib Artes, A
Added 24 Jun 2010
Updated 24 Jun 2010
Type Conference
Year 2005
Where CBMS
Authors Jin Yu, Syed Sibte Raza Abidi, Paul Habib Artes, Andrew R. McIntyre, Malcolm I. Heywood
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