Measurement of retinal vessel widths from fundus images based on 2-D modeling

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

Documents
Lowell2004TMIMeasurementOfRetinalVesselWidthsFromFundusImagesBasedOn2DModeling.pdf
[img]
[Download]
[img]
Preview
PDF
Lowell2004TMIMeasurementOfRetinalVesselWidthsFromFundusImagesBasedOn2DModeling.pdf - Whole Document

409kB

Official URL: http://dx.doi.org/10.1109/TMI.2004.830524

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 Science > School of Computer Science
ID Code:1216
Deposited By: Bev Jones
Deposited On:21 Sep 2007
Last Modified:13 Mar 2013 08:25

Repository Staff Only: item control page