An Image-Based Catheter Segmentation Algorithm for Optimized Electrophysiology Procedure Workflow

  • Maxime Cazalas
  • Vincent Bismuth
  • Régis Vaillant
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7945)


Electrophysiology ablation procedures are performed in an interventional lab. The therapy is delivered through several catheters introduced in cardiac chambers under x-ray guidance. They are also be used to measure some local electrical properties which can be color-coded. A kind of color-map is then established and it can be overlaid to images of the anatomy obtained with fluoroscopy.

A potential improvement in the workflow of the procedure may be reached by tracking the location of the tip of the catheter performing the measurement. We propose here an image-based strategy to detect it and we report the results obtained on a large clinical database. We segment the object of interest by selecting contrasted objects and we characterize them by taking into account all possible co founding factors. A selection strategy has been defined from the distribution of the found values for the true positive and false positive elements in a first clinical database (3000 images from a single site). We got a success rate for the detection of the target object of 86% on a larger database formed of about 4500 images coming from 7 different sites. We also developed an active learning strategy for improving the performance of the algorithm and its stability in the field. The principle is to take into account the user’s manual correction made on a given frame when processing the following ones, which is adapted to the clinical workflow: the segmentation result is assessed and corrected by an operator for each frame. We then gained additional 6% up to 91% on the success rate: the number of algorithm mistakes to be corrected by the operator is reduced to an acceptable level.


catheter detection ablation catheter RF ablation x-ray imaging image segmentation 


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  1. 1.
    Franken, E., Rongen, P.M.P., van Almsick, M., ter Haar Romeny, B.M.: Detection of electrophysiology catheters in noisy fluoroscopy images. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol. 4191, pp. 25–32. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  2. 2.
    Schenderlein, M., Dietmayer, K.: Image-based catheter tip tracking during cardiac ablation therapy. Methods, 1–5 (2010)Google Scholar
  3. 3.
    Buck, S.D., Ector, J., Gerche, A.L., Maes, F., Heidbchel, H.: Toward image-based catheter tip tracking for treatment of atrial fibrillation. In: CI2BM 2009 MICCAI Workshop on Cardiovascular Interventional Imaging and Biophysical Modelling (2009)Google Scholar
  4. 4.
    Brost, A., Liao, R., Strobel, N., Hornegger, J.: Respiratory motion compensation by model-based catheter tracking during EP procedures. Medical Image Analysis 14(5), 695–706 (2010)CrossRefGoogle Scholar
  5. 5.
    Hoffmann, M., Brost, A., Jakob, C., Bourier, F., Koch, M., Kurzidim, K., Hornegger, J., Strobel, N.: Semi-automatic catheter reconstruction from two views. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds.) MICCAI 2012, Part II. LNCS, vol. 7511, pp. 584–591. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  6. 6.
    Ma, Y., King, A.P., Gogin, N., Rinaldi, C.A., Gill, J., Razavi, R., Rhode, K.S.: Real-time respiratory motion correction for cardiac electrophysiology procedures using image-based coronary sinus catheter tracking. In: Jiang, T., Navab, N., Pluim, J.P.W., Viergever, M.A. (eds.) MICCAI 2010, Part I. LNCS, vol. 6361, pp. 391–399. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  7. 7.
    Wang, P., Zheng, Y., John, M., Comaniciu, D.: Catheter tracking via online learning for dynamic motion compensation in transcatheter aortic valve implantation. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds.) MICCAI 2012, Part II. LNCS, vol. 7511, pp. 17–24. Springer, Heidelberg (2012)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Maxime Cazalas
    • 1
  • Vincent Bismuth
    • 1
  • Régis Vaillant
    • 1
  1. 1.GEHCBucFrance

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