Automatic Initialization and Failure Detection for Surgical Tool Tracking in Retinal Microsurgery
Abstract
Instrument tracking is a key step for various computer-aidedinterventions in retinal microsurgery. One of the bottlenecks of state-of-the-art template based algorithms is the (re-)initialization during the surgery. We propose an algorithm for robustly detecting the bounding box around the tool tip together with a failure detection of the tracking algorithm. Hereby, the user input dependent algorithm is transformed into a completely automatic framework without the need of an assistant. The performance was compared to two state-of-the-art methods.