Registration with Adjacent Anatomical Structures for Cardiac Resynchronization Therapy Guidance

  • Daniel Toth
  • Maria Panayiotou
  • Alexander Brost
  • Jonathan M. Behar
  • Christopher A. Rinaldi
  • Kawal S. Rhode
  • Peter Mountney
Conference paper

DOI: 10.1007/978-3-319-52718-5_14

Part of the Lecture Notes in Computer Science book series (LNCS, volume 10124)
Cite this paper as:
Toth D. et al. (2017) Registration with Adjacent Anatomical Structures for Cardiac Resynchronization Therapy Guidance. In: Mansi T., McLeod K., Pop M., Rhode K., Sermesant M., Young A. (eds) Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges. STACOM 2016. Lecture Notes in Computer Science, vol 10124. Springer, Cham

Abstract

The clinical applications and benefits of multi-modal image registration are wide-ranging and well established. Current image based approaches exploit cross-modality information, such as landmarks or anatomical structures, which is visible in both modalities. A lack of cross-modality information can prohibit accurate automatic registration. This paper proposes a novel approach for MR to X-ray image registration which uses prior knowledge of adjacent anatomical structures to enable registration without cross-modality image information. The registration of adjacent structures formulated as a partial surface registration problem which is solved using a globally optimal ICP method. The practical clinical application of the approach is demonstrated on an image guided cardiac resynchronization therapy procedure. The left ventricle (segmented from pre-operative MR) is registered to the coronary vessel tree (extracted from intra-operative fluoroscopic images). The proposed approach is validated on synthetic and phantom data, where the results show a good comparison with the ground truth registrations. The vertex-to-vertex MAE was \(3.28\pm 1.18\) mm for 10 X-ray image pairs of the phantom.

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Daniel Toth
    • 1
    • 2
  • Maria Panayiotou
    • 2
  • Alexander Brost
    • 3
  • Jonathan M. Behar
    • 2
    • 4
  • Christopher A. Rinaldi
    • 2
    • 4
  • Kawal S. Rhode
    • 2
  • Peter Mountney
    • 5
  1. 1.Siemens Healthcare Ltd.CamberleyUK
  2. 2.Division of Imaging Sciences and Biomedical EngineeringKing’s College LondonLondonEngland, UK
  3. 3.Siemens Healthcare GmbHErlangenGermany
  4. 4.Department of CardiologyGuy’s and St. Thomas’ Hospitals NHS Foundation TrustLondonUK
  5. 5.Medical Imaging Technologies, Siemens HealthcarePrincetonUSA

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