Chapter

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007

Volume 4792 of the series Lecture Notes in Computer Science pp 94-101

Towards Subject-Specific Models of the Dynamic Heart for Image-Guided Mitral Valve Surgery

  • Cristian A. LinteAffiliated withBiomedical Engineering Graduate Program, University of Western OntarioImaging Research Laboratories, Robarts Research Institute
  • , Marcin WierzbickiAffiliated withImaging Research Laboratories, Robarts Research Institute
  • , John MooreAffiliated withImaging Research Laboratories, Robarts Research Institute
  • , Stephen H. LittleAffiliated withDivision of Cardiology, University of Western OntarioCanadian Surgical Technologies & Advanced Robotics London ON
  • , Gérard M. GuiraudonAffiliated withBiomedical Engineering Graduate Program, University of Western OntarioCanadian Surgical Technologies & Advanced Robotics London ON
  • , Terry M. PetersAffiliated withBiomedical Engineering Graduate Program, University of Western OntarioImaging Research Laboratories, Robarts Research Institute

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Abstract

Surgeons need a robust interventional system capable of providing reliable, real-time information regarding the position and orientation of the surgical targets and tools to compensate for the lack of direct vision and to enhance manipulation of intracardiac targets during minimally-invasive, off-pump cardiac interventions. In this paper, we describe a novel method for creating dynamic, pre-operative, subject-specific cardiac models containing the surgical targets and surrounding anatomy, and how they are used to augment the intra-operative virtual environment for guidance of valvular interventions. The accuracy of these pre-operative models was established by comparing the target registration error between the mitral valve annulus characterized in the pre-operative images and their equivalent structures manually extracted from 3D US data. On average, the mitral valve annulus was extracted with a 3.1 mm error across all cardiac phases. In addition, we also propose a method for registering the pre-operative models into the intra-operative virtual environment.