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VURTIGO: Visualization Platform for Real-Time, MRI-Guided Cardiac Electroanatomic Mapping

  • Conference paper
Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges (STACOM 2011)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7085))

Abstract

Guidance of electrophysiological (EP) procedures by magnetic resonance imaging (MRI) has significant advantages over x-ray fluoroscopy. Display of electroanatomic mapping (EAM) during an intervention fused with a prior MR volume and DE-MRI derived tissue classification should improve the accuracy of cardiac resynchronization therapy (CRT) for ventricular arrhythmias. Improved accuracy in the spatial localization of recorded EP points will produce an EAM to constrain and customize patient-specific cardiac electroanatomic models being developed for understanding the patterns of arrhythmogenic slow conduction zones causing reentry circuits and treatment planning. The Vurtigo software presented here is a four dimensional (3D+time) real-time visualization application for guiding interventions capable of displaying prior volumes, real-time MRI scan planes, EAM (voltage or activation times), segmented models, and tracked catheters. This paper will describe the architecture and features of Vurtigo followed by the application example of guiding percutaneous cardiac electroanatomic mapping in porcine models.

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Author information

Authors and Affiliations

  1. Imaging Research, Sunnybrook Health Sciences Centre, Canada

    Perry E. Radau, Stefan Pintilie, Roey Flor, Labonny Biswas, Samuel O. Oduneye, Venkat Ramanan, Kevan A. Anderson & Graham A. Wright

  2. Medical Biophysics, University of Toronto, Canada

    Samuel O. Oduneye, Kevan A. Anderson & Graham A. Wright

Authors
  1. Perry E. Radau
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  2. Stefan Pintilie
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  3. Roey Flor
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  4. Labonny Biswas
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  5. Samuel O. Oduneye
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  6. Venkat Ramanan
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  7. Kevan A. Anderson
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  8. Graham A. Wright
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Editor information

Editors and Affiliations

  1. Department of Information and Communication Technologies, University of Pompeu Fabra, Center for ComputationalImaging and Simulation Technologies in Biomedicine (CISTIB), Plaça de la Mercè 10-12, 08002, Barcelona, Spain

    Oscar Camara

  2. Machine Learning and Perception, Microsoft Research, 7 J J Thomson Avenue, CB3 0FB, Cambridge, UK

    Ender Konukoglu

  3. Department of Medical Biophysics, Ontario Cancer Institute, princess Margaret Hospital, University of Toronto, Faculty of Medicien, 610 University Avenue, M5G 2M9, Toronto, ON, Canada

    Mihaela Pop

  4. Division of Imaging Sciences, King’s College London, St. Thomas Hospital, Lambeth Wing, SE1 7EH, London, UK

    Kawal Rhode

  5. Research Centre, Ascöepios Team, Inria Sophia Antipolis- Méditerranée, 2004 Route des Lucioles, BP 93, 06902, Sophia Antipolis Cedex, France

    Maxime Sermesant

  6. Auckland Bioengineering Institute, Medical and Health Sciences, University of Auckland, Grafton Campus, Building 502, Auckland, New Zealand

    Alistair Young

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© 2012 Springer-Verlag Berlin Heidelberg

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Radau, P.E. et al. (2012). VURTIGO: Visualization Platform for Real-Time, MRI-Guided Cardiac Electroanatomic Mapping. In: Camara, O., Konukoglu, E., Pop, M., Rhode, K., Sermesant, M., Young, A. (eds) Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges. STACOM 2011. Lecture Notes in Computer Science, vol 7085. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28326-0_25

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  • DOI: https://doi.org/10.1007/978-3-642-28326-0_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28325-3

  • Online ISBN: 978-3-642-28326-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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