Unified detection and tracking in retinal microsurgery.

Raphael Sznitman, Anasuya Basu, Rogerio Richa, Jim Handa, Peter Gehlbach, Russell H. Taylor, Bruno Jedynak, Gregory D. Hager

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)1-8
Number of pages8
JournalMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Volume14
Issue numberPt 1
StatePublished - 2011
Externally publishedYes

ASJC Scopus subject areas

  • Medicine(all)

Fingerprint Dive into the research topics of 'Unified detection and tracking in retinal microsurgery.'. Together they form a unique fingerprint.

Cite this