Lowell, J. and Hunter, Andrew and Steel, D. and Basu, A. and Ryder, R. and Kennedy, R. L. (2004) Measurement of retinal vessel widths from fundus images based on 2-D modeling. Medical Imaging, IEEE Transactions on, 23 (10). pp. 1196-1204. ISSN UNSPECIFIED

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Abstract

Changes in retinal vessel diameter are an important sign of diseases such as hypertension, arteriosclerosis and diabetes mellitus. Obtaining precise measurements of vascular widths is a critical and demanding process in automated retinal image analysis as the typical vessel is only a few pixels wide. This paper presents an algorithm to measure the vessel diameter to subpixel accuracy. The diameter measurement is based on a two-dimensional difference of Gaussian model, which is optimized to fit a two-dimensional intensity vessel segment. The performance of the method is evaluated against Brinchmann-Hansen's half height, Gregson's rectangular profile and Zhou's Gaussian model. Results from 100 sample profiles show that the presented algorithm is over 30% more precise than the compared techniques and is accurate to a third of a pixel.

Item Type:	Article
Additional Information:	Changes in retinal vessel diameter are an important sign of diseases such as hypertension, arteriosclerosis and diabetes mellitus. Obtaining precise measurements of vascular widths is a critical and demanding process in automated retinal image analysis as the typical vessel is only a few pixels wide. This paper presents an algorithm to measure the vessel diameter to subpixel accuracy. The diameter measurement is based on a two-dimensional difference of Gaussian model, which is optimized to fit a two-dimensional intensity vessel segment. The performance of the method is evaluated against Brinchmann-Hansen's half height, Gregson's rectangular profile and Zhou's Gaussian model. Results from 100 sample profiles show that the presented algorithm is over 30% more precise than the compared techniques and is accurate to a third of a pixel.
Keywords:	Retinal screening, computer vision
Subjects:	G Mathematical and Computer Sciences > G400 Computer Science G Mathematical and Computer Sciences > G740 Computer Vision
Divisions:	College of Sciences > Faculty of Science > Lincoln School of Computer Science
Depositing User:	Bev Jones
Date Deposited:	21 Sep 2007
Last Modified:	13 Mar 2013 08:25
URI:	http://eprints.lincoln.ac.uk/id/eprint/1216

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