RETINAL VASCULAR TREE CONSTRUCTION WITH MULTIMODAL FLUORESCEIN ANGIOGRAM SEQUENCE

Abstract

In this article, we present a method to construct retinal vascular tree with the spatial information and temporal intensity profile of vessels. The significance of the work is to assist in clinical studies of diagnosis of cardiovascular diseases, such as hypertension, which manifest abnormalities in either venous and/or arterial vascular systems. For temporal intensity profile, fluorescein angiogram (FA) is adopted to ensure continuity of vessel segments along time. We separate retinal vascular tree construction into two main steps — vessel extraction and vessel grouping. In vessel extraction, we use an existing algorithm that applies multiscale matched filtering and vessel likelihood measure to extract vessel segments and its spatial information in color retinal image. Vessel segments are grouped using extended Kalman filter to take into consideration continuities in curvature, width, and fluorescein angiogram sequence changes at the bifurcation or crossover point. The algorithm is evaluated on a clinical data set from Taipei Veterans' General Hospital, and the results are compared with the ground truth images provided by a physician. The results show that our method reaches an average correctness rate of 91.48%.