Abstract
Tortuosity is among the first alterations in retinal vessel network to appear in many retinopathies. Automatic evaluation of retinal vessel tortuosity is thus a valuable tool for early detection of vascular suffering. Quite a few techniques for tortuosity measurement and classification have been proposed, but they do not always match the clinical concept of tortuosity. This justifies the need for a new definition, able to express in mathematical terms the tortuosity as perceived by ophthalmologists. We propose here a new algorithm for the evaluation of tortuosity in vessels extracted from digital fundus images. It is based on the partitioning of each vessel in segments of constant-sign curvature and on the combination between the number of such segments and their curvature values. This algorithm has been compared with the other tortuosity measures on a set of 20 vessels from 10 different images. These vessels had been preliminarily ordered by an expert ophthalmologist in order of increasing perceived tortuosity. The proposed algorithm proved to be the best one as regards arterial tortuosity and among the best for vein tortuosity evaluation.
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