Computer algorithms for the automated measurement of retinal arteriolar diameters

Aims-Quantification of retinal vascular change is difficult and manual meas urements 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 vesse l 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 linea r regression filter (SLRF). Method agreement was analysed using Bland-Altma n 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 t han those measured manually. The SLRF method was the most repeatable and th e 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 arte riolar diameter. Application of automated methods of retinal vascular analy sis may be useful in the assessment of cardiovascular and other diseases.