Multi-scale Retinal Vessel Tortuosity Measurement Based on Wavelet Transform

The presence of tortuosity in the retinal vessels is crucial in the diagnosis of ocular fundus disorders. There are numerous methods for computing the tortuosity of the retinal arteries available today, all of which have yielded impressive results. However, they usually divide vessels into smaller vascular structures to calculate local tortuosities, which are then weighted summed to get the global tortuosity of the entire vessel. The approach of local division on a two-dimensional image weakens local vessel tortuosity information and makes it unable to accurately portray the vessel's tortuosity. Hence, we propose a wavelet transform-based multi-scale approach for evaluating the tortuosity of fundus vessels in order to investigate the differences between normal and pathological vessels in terms of spatial tortuous properties. To acquire the skeleton of the fundus vessels, we apply the Zhang-Suen method to refine retinal vessel images segregated by experts. The vascular skeletons are then converted into one-dimension signals, on which we carry out a wavelet transform to yield vascular tortuosity of different scales, which is further evaluated with entropy. The results of the experiments reveal that the suggested tortuosity measure can effectively classify the curvature of blood vessel segments and blood vessel networks.