A Virtual Exploring Robot for Adaptive Left Ventricle Contour Detection in Cardiac MR Images (original) (raw)

Abstract

This paper presents an original knowledge driven automatic contour detection approach based on neuro-fuzzy techniques. The method simulates a trained virtual autonomous mobile robot that delineates the organ outlines by combining local image information and global a-priori shape knowledge. In a pilot validation study into left ventricular delineation in cardiac MR images, our novel method demonstrated a high robustness, and a clinically acceptable border localization performance.

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Authors and Affiliations

  1. Div. of Image Processing, Dept of Radiology, C2S, Leiden University Medical Center, P.O. Box 9600, 2300, RC, Leiden, The Netherlands
    F. Behloul, B.P.F. Lelieveldt, R. J. van der Geest & J. H. C. Reiber

Authors

  1. F. Behloul
  2. B.P.F. Lelieveldt
  3. R. J. van der Geest
  4. J. H. C. Reiber

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Editors and Affiliations

  1. Image Sciences Institute, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
    Wiro J. Niessen & Max A. Viergever &

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© 2001 Springer-Verlag Berlin Heidelberg

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Behloul, F., Lelieveldt, B., van der Geest, R.J., Reiber, J.H.C. (2001). A Virtual Exploring Robot for Adaptive Left Ventricle Contour Detection in Cardiac MR Images. In: Niessen, W.J., Viergever, M.A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2001. MICCAI 2001. Lecture Notes in Computer Science, vol 2208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45468-3\_197

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