A novel approach for quantification of retinal vessel tortuosity based on principal component analysis

Tortuosity is one of the first manifestations of many retinal diseases such as those due to retinopathy of prematurity (ROP), hypertension, stroke, diabetes and cardiovascular diseases. An automatic evaluation and quantification of retinal vessel tortuosity would help in the early detection of such retinopathies and other systemic diseases. This paper proposes a new approach based on principal component analysis (PCA), for the evaluation of tortuosity in vessels extracted from digital fundus images. One of the strength of the proposed algorithm is that the index is independent of translation, rotation and scaling. Measures are adopted such that the proposed approach matches with the clinical concept of tortuosity. The algorithm is compared with other available tortuosity measures. We have demonstrated its validity as an indicator of changes in morphology using simulated shapes. It is superior to other putative indices, presented previously in literature.