Real-Time Active Shape Models for Segmentation of 3D Cardiac Ultrasound

  • Jøger Hansegård
  • Fredrik Orderud
  • Stein I. Rabben
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4673)

Abstract

We present a fully automatic real-time algorithm for robust and accurate left ventricular segmentation in three-dimensional (3D) cardiac ultrasound. Segmentation is performed in a sequential state estimation fashion using an extended Kalman filter to recursively predict and update the parameters of a 3D Active Shape Model (ASM) in real-time. The ASM was trained by tracing the left ventricle in 31 patients, and provided a compact and physiological realistic shape space. The feasibility of the proposed algorithm was evaluated in 21 patients, and compared to manually verified segmentations from a custom-made semi-automatic segmentation algorithm. Successful segmentation was achieved in all cases. The limits of agreement (mean±1.96SD) for the point-to-surface distance were 2.2±1.1mm. For volumes, the correlation coefficient was 0.95 and the limits of agreement were 3.4±20 ml. Real-time segmentation of 25 frames per second was achieved with a CPU load of 22%.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Jøger Hansegård
    • 1
  • Fredrik Orderud
    • 2
  • Stein I. Rabben
    • 3
  1. 1.University of OsloNorway
  2. 2.Norwegian University of Science and TechnologyNorway
  3. 3.GE Vingmed UltrasoundNorway

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