Multi-modal imaging, model-based tracking, and mixed reality visualisation for orthopaedic surgery

Sing Chun Lee, Bernhard Fuerst, Keisuke Tateno, Alex Johnson, Javad Fotouhi, Greg Osgood, Federico Tombari, Nassir Navab

Research output: Contribution to journalArticle

Abstract

Orthopaedic surgeons are still following the decades old workflow of using dozens of two-dimensional fluoroscopic images to drill through complex 3D structures, e.g. pelvis. This Letter presents a mixed reality support system, which incorporates multi-modal data fusion and model-based surgical tool tracking for creating a mixed reality environment supporting screw placement in orthopaedic surgery. A red-green-blue-depth camera is rigidly attached to a mobile C-arm and is calibrated to the cone-beam computed tomography (CBCT) imaging space via iterative closest point algorithm. This allows real-time automatic fusion of reconstructed surface and/or 3D point clouds and synthetic fluoroscopic images obtained through CBCT imaging. An adapted 3D model-based tracking algorithm with automatic tool segmentation allows for tracking of the surgical tools occluded by hand. This proposed interactive 3D mixed reality environment provides an intuitive understanding of the surgical site and supports surgeons in quickly localising the entry point and orienting the surgical tool during screw placement. The authors validate the augmentation by measuring target registration error and also evaluate the tracking accuracy in the presence of partial occlusion.

Original languageEnglish (US)
Pages (from-to)168-173
Number of pages6
JournalHealthcare Technology Letters
Volume4
Issue number5
DOIs
StatePublished - Jan 1 2017

ASJC Scopus subject areas

  • Health Informatics
  • Health Information Management

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