UNSPECIFIED (2002) Detecting branching structures using local gaussian models. In: IEEE International Symposium on Biomedical Imaging, JUL 07-10, 2002, WASHINGTON, D.C..

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Abstract

We present a method for modelling and estimating branching structures, such as blood vessel bifurcations, from medical images. Branches are modelled as a superposition of Gaussian functions in a local region which describe the amplitude, position and orientations of intersecting linear features. The centroids of component features are separated by applying K-means to the local Fourier phase and the covariances and amplitudes subsequently estimated by a likelihood maximisation. We employ a penalised likelihood test (AIC) to select the best fit model in a region. Results are presented on synthetic and representative 2D retinal images which show the estimation to be robust and accurate in the presence of noise. We compare our results with a curvature scale-space operator method.

Item Type:	Conference Item (UNSPECIFIED)
Subjects:	R Medicine T Technology > TK Electrical engineering. Electronics Nuclear engineering
Journal or Publication Title:	2002 IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING, PROCEEDINGS
Publisher:	IEEE
ISBN:	0-7803-7584-X
Date:	2002
Number of Pages:	4
Page Range:	pp. 161-164
Publication Status:	Published
Title of Event:	IEEE International Symposium on Biomedical Imaging
Location of Event:	WASHINGTON, D.C.
Date(s) of Event:	JUL 07-10, 2002
URI:	http://wrap.warwick.ac.uk/id/eprint/10312

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