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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 (Unpublished)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 | ||||
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Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software | ||||
Divisions: | Faculty of Science, Engineering and Medicine > 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: |
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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Publication Status: | Unpublished | ||||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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