Computer algorithms for the automated measurement of retinal arteriolar diameters

AIMS Quantification of retinal vascular change is difficult and manual measurements of vascular features are slow and subject to observer bias. These problems may be overcome using computer algorithms. Three automated methods and a manual method for measurement of arteriolar diameters from digitised...

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Vydáno v:British journal of ophthalmology Ročník 85; číslo 1; s. 74 - 79
Hlavní autoři: Chapman, N, Witt, N, Gao, X, Bharath, A A, Stanton, A V, Thom, S A, Hughes, A D
Médium: Journal Article
Jazyk:angličtina
Vydáno: BMA House, Tavistock Square, London, WC1H 9JR BMJ Publishing Group Ltd 01.01.2001
BMJ
BMJ Publishing Group LTD
Témata:
Adult
Aged
Aged, 80 and over
Algorithms
Arterioles - anatomy & histology
automated measurement
Automation
Biological and medical sciences
Cardiovascular disease
computer algorithms
Female
Fluorescein Angiography
Geometry
Humans
Hypertension
Image Processing, Computer-Assisted - methods
Linear Models
Male
Measurement techniques
Medical sciences
Methods
Middle Aged
Mortality
Ophthalmology
Original articles - Laboratory science
Photography
Regression analysis
Reproducibility of Results
retinal arteriolar diameters
Retinal Artery - anatomy & histology
Retinopathies
Human
Hypertension
Measurement
Evaluation
Retinopathy
Arteriole
Cardiovascular disease
Retina
Algorithm
Automated processing
Eye disease
Computer aid
Diameter
ISSN:0007-1161, 1468-2079
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Shrnutí:AIMS Quantification of retinal vascular change is difficult and manual measurements of vascular features are slow and subject to observer bias. These problems may be overcome using computer algorithms. Three automated methods and a manual method for measurement of arteriolar diameters from digitised red-free retinal photographs were compared. METHODS 60 diameters (in pixels) measured by manual identification of vessel edges in red-free retinal images were compared with diameters measured by (1) fitting vessel intensity profiles to a double Gaussian function by non-linear regression, (2) a standard edge detection algorithm (Sobel), and (3) determination of points of maximum intensity variation by a sliding linear regression filter (SLRF). Method agreement was analysed using Bland–Altman plots and the repeatability of each method was assessed. RESULTS Diameter estimations obtained using the SLRF method were the least scattered although diameters obtained were approximately 3 pixels greater than those measured manually. The SLRF method was the most repeatable and the Gaussian method less so. The Sobel method was the least consistent owing to frequent misinterpretation of the light reflex as the vessel edge. CONCLUSION Of the three automated methods compared, the SLRF method was the most consistent (defined as the method producing diameter estimations with the least scatter) and the most repeatable in measurements of retinal arteriolar diameter. Application of automated methods of retinal vascular analysis may be useful in the assessment of cardiovascular and other diseases.
Bibliografie:istex:32F80AA2668ACE064B839ADF8FCE9BD44E231BC3
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href:bjophthalmol-85-74.pdf
PMID:11133716
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ISSN:0007-1161
1468-2079
DOI:10.1136/bjo.85.1.74