Hybrid tracking and mosaicking for information augmentation in retinal surgery

Current technical limitations in retinal surgery hinder the ability of surgeons to identify and localize surgical targets, increasing operating times and risks of surgical error. In this paper we present a hybrid tracking and mosaicking method for augmented reality in retinal surgery. The system is a combination of direct and feature-based tracking methods. A novel extension for direct visual tracking using a robust image similarity measure in color images is also proposed. Several experiments conducted on phantom, in vivo rabbit and human images attest the ability of the method to cope with the challenging retinal surgery scenario. Applications of the proposed method for tele-mentoring and intra-operative guidance are demonstrated.