Semiautomatic volume conductor modeling pipeline for imaging the cardiac electrophysiology noninvasively

  • Authors:

  • Bernhard Pfeifer;Michael Seger;Christoph Hintermüller;Gerald Fischer;Friedrich Hanser;Robert Modre;Hannes Mühlthaler;Bernhard Tilg

  • Affiliations:

  • Institute of Biomedical Engineering, University for Health sciences, medical informatics and technology, Austria;Institute of Biomedical Engineering, University for Health sciences, medical informatics and technology, Austria;Institute of Biomedical Engineering, University for Health sciences, medical informatics and technology, Austria;Institute of Biomedical Engineering, University for Health sciences, medical informatics and technology, Austria;Institute of Biomedical Engineering, University for Health sciences, medical informatics and technology, Austria;ARC Seibersdorf research GmbH, Austria;Department of Vascular Surgery, Innsbruck Medical University, Innsbruck;Institute of Biomedical Engineering, University for Health sciences, medical informatics and technology, Austria

  • Venue:
  • MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
  • Year:
  • 2006

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Abstract

In this paper we present an approach for extracting patient individual volume conductor models (VCM) using volume data acquired from Magnetic Resonance Imaging (MRI) for computational biology of electrical excitation in the patient’s heart. The VCM consists of the compartments chest surface, lung surfaces, the atrial and ventricular myocardium, and the blood masses. For each compartment a segmentation approach with no or little necessity of user interaction was implemented and integrated into a VCM segmentation pipeline to enable the inverse problem of electrocardiography to become clinical applicable. The segmentation pipeline was tested using volume data from ten patients with structurally normal hearts.