International Conference on Medical Image Computing and Computer-Assisted Intervention

MICCAI 2011: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011 pp 161-168

Image-Based Device Tracking for the Co-registration of Angiography and Intravascular Ultrasound Images

  • Peng Wang
  • Terrence Chen
  • Olivier Ecabert
  • Simone Prummer
  • Martin Ostermeier
  • Dorin Comaniciu
Conference paper

DOI: 10.1007/978-3-642-23623-5_21

Volume 6891 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Wang P., Chen T., Ecabert O., Prummer S., Ostermeier M., Comaniciu D. (2011) Image-Based Device Tracking for the Co-registration of Angiography and Intravascular Ultrasound Images. In: Fichtinger G., Martel A., Peters T. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011. MICCAI 2011. Lecture Notes in Computer Science, vol 6891. Springer, Berlin, Heidelberg

Abstract

The accurate and robust tracking of catheters and transducers employed during image-guided coronary intervention is critical to improve the clinical workflow and procedure outcome. Image-based device detection and tracking methods are preferred due to the straightforward integration into existing medical equipments. In this paper, we present a novel computational framework for image-based device detection and tracking applied to the co-registration of angiography and intravascular ultrasound (IVUS), two modalities commonly used in interventional cardiology. The proposed system includes learning-based detections, model-based tracking, and registration using the geodesic distance. The system receives as input the selection of the coronary branch under investigation in a reference angiography image. During the subsequent pullback of the IVUS transducers, the system automatically tracks the position of the medical devices, including the IVUS transducers and guiding catheter tips, under fluoroscopy imaging. The localization of IVUS transducers and guiding catheter tips is used to continuously associate an IVUS imaging plane to the vessel branch under investigation. We validated the system on a set of 65 clinical cases, with high accuracy (mean errors less than 1.5mm) and robustness (98.46% success rate). To our knowledge, this is the first reported system able to automatically establish a robust correspondence between the angiography and IVUS images, thus providing clinicians with a comprehensive view of the coronaries.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Peng Wang
    • 1
  • Terrence Chen
    • 1
  • Olivier Ecabert
    • 2
  • Simone Prummer
    • 2
  • Martin Ostermeier
    • 2
  • Dorin Comaniciu
    • 1
  1. 1.Siemens Corporate ResearchSiemens CorporationPrincetonUSA
  2. 2.Healthcare SectorSiemens AGForchheimGermany