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Detecting branching structures using local Gaussian models

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Wang, Li and Bhalerao, Abhir (2002) Detecting branching structures using local Gaussian models. University of Warwick. Department of Computer Science. (Department of Computer Science research report). (Unpublished)

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Abstract

This report presents a method of detecting branching structure, such as blood vessels from retinal images, using a Gaussian Intensity model. Features are modelled with a Gaussian function parameterised by position, orientation and variance within some spatial window. Multiple features are modelled using a superposition of Gaussian models. A non-parametric classifier (k-means) is used to cluster components corresponding to each feature. Two different groups of images are used to test the methodology: artificial images and images of the human retina.

Item Type: Report
Subjects: Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Divisions: Faculty of Science > Computer Science
Library of Congress Subject Headings (LCSH): Image processing -- Digital techniques, Diagnostic imaging, Blood-vessels
Series Name: Department of Computer Science research report
Publisher: University of Warwick. Department of Computer Science
Official Date: 26 November 2002
Dates:
DateEvent
26 November 2002Published
Number: Number 385
Number of Pages: 23
DOI: CS-RR-385
Institution: University of Warwick
Theses Department: Department of Computer Science
Status: Peer Reviewed
Publication Status: Unpublished
Funder: Engineering and Physical Sciences Research Council (EPSRC)
Grant number: GR/M82899 (EPSRC)
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