3D Reconstruction of Coronary Veins from a Single X-Ray Fluoroscopic Image and Pre-operative MR View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2017

AUTHORS

Maria Panayiotou , Daniel Toth , Tamer Adem , Peter Mountney , Alexander Brost , Jonathan M. Behar , C. Aldo Rinaldi , R. James Housden , Kawal S. Rhode

ABSTRACT

Cardiac resynchronization therapy (CRT) is an effective treatment for patients with congestive heart failure and ventricular dyssynchrony. Despite the overall efficacy of CRT, approximately 30% of patients receiving CRT do not improve. One of the main technical problems related to the CRT procedure is inadequate visualisation in X-ray fluoroscopy of the venous anatomy in relation to accurate cardiac chamber visualisation. This paper proposes a novel approach for 3D reconstruction of coronary veins from a single contrast enhanced intra-operative fluoroscopy image. For this application, the method uses back-projection geometry and a Euclidean distance/angle-based cost function. The algorithm is validated on a phantom and five patient datasets, comprising six view-angle orientations for the phantom dataset and two view-angle orientations for each of the patient datasets. Median(inter-quartile range) 3D-reconstruction accuracies of 1.41(0.55–3.00) mm and 3.28(2.10–4.89) mm were established for the phantom and patient data, respectively. The technique can facilitate careful advancement of the cannulating guide over a guidewire or a diagnostic catheter positioned in the coronary sinus, and consequently, improve the chances of response to CRT. More... »

PAGES

66-75

References to SciGraph publications

  • 2000-12. 3D coronary reconstruction from routine single-plane coronary angiograms: Clinical validation and quantitative analysis of the right coronary artery in 100 patients in THE INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING
  • 2012. Automatic Segmentation of the Myocardium in Cine MR Images Using Deformable Registration in STATISTICAL ATLASES AND COMPUTATIONAL MODELS OF THE HEART. IMAGING AND MODELLING CHALLENGES
  • Book

    TITLE

    Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges

    ISBN

    978-3-319-52717-8
    978-3-319-52718-5

    From Grant

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-319-52718-5_8

    DOI

    http://dx.doi.org/10.1007/978-3-319-52718-5_8

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1074215753


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