Measurement of retinal vessel widths from fundus images based on 2-D modeling.
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.
Lowell
James
J
Department of Applied Computer Science, University of Lincoln, Brayford Pools, Lincoln LN6 7TS, U.K.
Hunter
Andrew
A
Steel
David
D
Basu
Ansu
A
Ryder
Robert
R
Kennedy
R Lee
RL
D000465:Algorithms; D019412:Anatomy, Cross-Sectional / Q000379:methods*; D001185:Artificial Intelligence; D003198:Computer Simulation; D005451:Fluorescein Angiography / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D008954:Models, Biological; D015233:Models, Statistical; D009716:Numerical Analysis, Computer-Assisted; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012171:Retinal Vessels / Q000033:anatomy & histology*; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted