Unified detection and tracking in retinal microsurgery.

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

Research output: Chapter in Book/Report/Conference proceedingChapter

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)
Title of host publicationMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Pages1-8
Number of pages8
Volume14
EditionPt 1
StatePublished - 2011
Externally publishedYes

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ASJC Scopus subject areas

  • Medicine(all)

Cite this

Sznitman, R., Basu, A., Richa, R., Handa, J., Gehlbach, P., Taylor, R. H., Jedynak, B., & Hager, G. (2011). Unified detection and tracking in retinal microsurgery. In Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention (Pt 1 ed., Vol. 14, pp. 1-8)