UNSPECIFIED (2003) Model based segmentation for retinal fundus images. In: 13th Scandinavian Conference on Image Analysis (SCIA 2003), JUN 29-JUL 02, 2003, HALMSTAD, SWEDEN.

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Abstract

This paper presents a method for detecting and measuring the vascular structures of retinal images. Features are modelled as a superposition of Gaussian functions in a local region. The parameters i.e. centroid, orientation, width of the feature are derived by a minimum mean square error (MMSE) type of spatial regression. We employ a penalised likelihood test, the Akakie Information Criteria (AIC), to select the best model and scale for vessel segments. A maximum-cost spanning tree (MST) algorithm is then used to perform the neighbourhood linking and infer the global vascular structure.. We present results of evaluations on a set of twenty digital fundus retinal images.

Item Type:	Conference Item (UNSPECIFIED)
Subjects:	Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Series Name:	LECTURE NOTES IN COMPUTER SCIENCE
Journal or Publication Title:	IMAGE ANALYSIS, PROCEEDINGS
Publisher:	SPRINGER-VERLAG BERLIN
ISBN:	3-540-40601-8
ISSN:	0302-9743
Editor:	Bigun, J and Gustavsson, T
Date:	2003
Volume:	2749
Number of Pages:	8
Page Range:	pp. 422-429
Publication Status:	Published
Title of Event:	13th Scandinavian Conference on Image Analysis (SCIA 2003)
Location of Event:	HALMSTAD, SWEDEN
Date(s) of Event:	JUN 29-JUL 02, 2003
URI:	http://wrap.warwick.ac.uk/id/eprint/9353

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