Retinal image registration using bifurcation structures

This paper presents a new structural feature for feature-based retinal image registration. The conventional point-matching methods largely depend on the branching angles of single bifurcation point. The feature correspondence across two images may not be unique due to the similar angle values. In view of this, structure-matching registration is favored. The bifurcation structure is composed of a master bifurcation point and its three connected neighbors. The characteristic vector of each bifurcation structure consists of the normalized branching angle and length, which is invariant against translation, rotation, scaling, and even modest distortion. This can greatly reduce the ill-posed nature of the matching process as long as the vasculature pattern can be segmented. The simplicity and efficiency of the proposed method make it readily to be applied alone or incorporated with other existing methods to formulate a hybrid or hierarchy scheme.