An automatic vessel diameter measurement technique based on linear discriminant analysis (LDA) has been proposed. After estimating the vessel wall, the vessel cross-section profile is divided into three regions: two corresponding to the background and one to the vessel. The algorithm was tested on more than 5000 cross-sections of retinal vessels from the REVIEW dataset through comparative study with the state-of-the-art techniques. Cross-correlation analyses were performed to determine the degree to which the proposed technique was close to the ground truth. The results indicate that proposed algorithm consistently performed better than most of other techniques and was highly correlated with the manual measurement as the reference diameter. The proposed method does not require any supervision and is suitable for automatic analysis. 1. Introduction Retina images allow noninvasive viewing of the in-vivo vessels and have been established as indicator for incidence of diabetic retinopathy [1, 2], early indicator of stroke [3, 4] and hypertension [5]. It is the best modality to see the microvascular abnormalities [6] such as change in the width of the vasculature. Changes in the width of the retinal arteriole and venules are known as direct indictors of retinal vasculature abnormality [7]; detection of which requires accurate measurement of retinal vessel diameter. However, complex background and uneven lighting conditions result in poor contrast at vessel edges [8], and this result in inaccurate diameter measurement. Several techniques have been published previously for vessel diameter estimation and edge delineation. Brinchmann-Hansen and Heier proposed the Half Height Full Width (HHFW) method in which the diameter was defined as the distance between the points on the vessel intensity cross-section profile where the function reaches 50% of its maximum value to either side of the estimated centre point [9]. Gregson et al. [10] fitted a rectangle to the vessel profile and estimated the width by setting the area under the curve equal to the area under the rectangle. In [11], the vessel profile was approximated by 1D Gaussian function based on the assumption that the intensity profile follows a symmetric Gaussian-like shape. This was further extended to 2D Gaussian by Lowell et al. [12] which was more robust compared to 1D Gaussian method. Gao et al. [13] established that the retinal vessel profile could be fitted with twin-Gaussian model. The study found a linear relationship between the standard deviation (SD) of the Gaussian and the gold standard diameters
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