Registration with Adjacent Anatomical Structures for Cardiac Resynchronization Therapy Guidance

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10124)


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.


Cardiac Resynchronization Therapy Iterative Close Point Vessel Tree Phantom Data Adjacent Anatomical Structure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Acknowledgements and Disclaimer

The authors are grateful for the support from the Innovate UK grant 32684-234174. The research was supported by the National Institute for Health Research (NIHR) Biomedical Research Centre based at Guys and St Thomas NHS Foundation Trust and Kings College London. The views expressed are those of the authors and not necessarily those of the NHS, NIHR or the Department of Health. Concepts and information presented are based on research and are not commercially available.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  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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