Adaptive Higuchi's dimension-based retinal vessel diameter measurement.

This paper proposes the use of an adaptive model to measure the width of retinal vessels in fundus photographs. It is based on the hypothesis that the Higuchi's dimension of the cross-section is proportional to the vessel diameter. This approach does not require image segmentation and binarization of the vessels and therefore is suitable for machine based measurements. The model is developed using a synthetic image of the vessel of known diameter and added noise. As a first step, the vessel cross-section profiles were manually obtained and analyzed using Higuchi's fractal dimension method. A 3D model was formed using the relationship between Higuchi's dimension, vessel diameter and noise variance. This model was then evaluated using expert annotated REVIEW public database and solved for the vessel diameter for performance evaluation. The result showed a good agreement with state of the art techniques. The model is background noise tolerant, estimates the vessel width with subpixel precision and does not require manual intervention.