title: Unified detection and tracking in retinal microsurgery.
abstract: Traditionally, tool tracking involves two subtasks: (i) detecting the tool in the initial image in which it appears, and (ii) predicting and refining the configuration of the detected tool in subsequent images. With retinal microsurgery in mind, we propose a unified tool detection and tracking framework, removing the need for two separate systems. The basis of our approach is to treat both detection and tracking as a sequential entropy minimization problem, where the goal is to determine the parameters describing a surgical tool in each frame. The resulting framework is capable of both detecting and tracking in situations where the tool enters and leaves the field of view regularly. We demonstrate the benefits of this method in the context of retinal tool tracking. Through extensive experimentation on a phantom eye, we show that this method provides efficient and robust tool tracking and detection.
authors: Johns Hopkins Univesity, 3400 N. Charles Str., Baltimore, USA. sznitman@jhu.edu
authors: Raphael
authors: R
authors: Sznitman
authors: Anasuya
authors: A
authors: Basu
authors: Rogerio
authors: R
authors: Richa
authors: Jim
authors: J
authors: Handa
authors: Peter
authors: P
authors: Gehlbach
authors: Russell H
authors: RH
authors: Taylor
authors: Bruno
authors: B
authors: Jedynak
authors: Gregory D
authors: GD
authors: Hager
mesh_terms: D000465:Algorithms; D019277:Entropy; D006801:Humans; D008866:Microsurgery / Q000379:methods*; D013508:Ophthalmologic Surgical Procedures; D015203:Reproducibility of Results; D012160:Retina / Q000601:surgery*; D025321:Surgery, Computer-Assisted / Q000379:methods