Fully Automatic Catheter Localization in C-Arm Images Using ℓ1-Sparse Coding

  • Fausto Milletari
  • Vasileios Belagiannis
  • Nassir Navab
  • Pascal Fallavollita
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8674)


We propose a method to perform automatic detection and tracking of electrophysiology (EP) catheters in C-arm fluoroscopy sequences. Our approach does not require any initialization, is completely automatic, and can concurrently track an arbitrary number of overlapping catheters. After a pre-processing step, we employ sparse coding to first detect candidate catheter tips, and subsequently detect and track the catheters. The proposed technique is validated on 2835 C-arm images, which include 39,690 manually selected ground-truth catheter electrodes. Results demonstrated sub-millimeter detection accuracy and real-time tracking performances.


Catheter Ablation Sparse Code Cardiac Electrophysiology Catheter Tracking Blob Detector 
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.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Fausto Milletari
    • 1
  • Vasileios Belagiannis
    • 1
  • Nassir Navab
    • 1
  • Pascal Fallavollita
    • 1
  1. 1.Chair for Computer Aided Medical ProceduresTechnical University of MunichGermany

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