Extraction of Cardiac and Respiratory Motion Information from Cardiac X-Ray Fluoroscopy Images Using Hierarchical Manifold Learning

  • Maria Panayiotou
  • Andrew P. King
  • Kanwal K. Bhatia
  • R. James Housden
  • YingLiang Ma
  • C. Aldo Rinaldi
  • Jas Gill
  • Michael Cooklin
  • Mark O’Neill
  • Kawal S. Rhode
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8330)

Abstract

We present a novel and clinically useful method to automatically determine the regions that carry cardiac and respiratory motion information directly from standard mono-plane X-ray fluoroscopy images. We demonstrate the application of our method for the purposes of retrospective cardiac and respiratory gating of X-ray images. Validation is performed on five mono-plane imaging sequences comprising a total of 284 frames from five patients undergoing radiofrequency ablation for the treatment of atrial fibrillation. We established end-inspiration, end-expiration and systolic gating with success rates of 100%, 100% and 95.3%, respectively. This technique is useful for retrospective gating of X-ray images and, unlike many previously proposed techniques, does not require specific catheters to be visible and works without any knowledge of catheter geometry.

Keywords

Catheter Manifold Respiration Unal Lasso 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Maria Panayiotou
    • 1
  • Andrew P. King
    • 1
  • Kanwal K. Bhatia
    • 3
  • R. James Housden
    • 1
  • YingLiang Ma
    • 1
  • C. Aldo Rinaldi
    • 1
    • 2
  • Jas Gill
    • 1
    • 2
  • Michael Cooklin
    • 1
    • 2
  • Mark O’Neill
    • 1
    • 2
  • Kawal S. Rhode
    • 1
  1. 1.Division of Imaging Sciences and Biomedical EngineeringKing’s College LondonUK
  2. 2.Department of Cardiology, Guy’s & St. Thomas’Hospitals NHS Foundation TrustLondonUK
  3. 3.Biomedical Image Analysis Group, Department of ComputingImperial College LondonLondonUK

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