Motion-Compensation of Cardiac Perfusion MRI Using a Statistical Texture Ensemble

  • Mikkel B. Stegmann
  • Henrik B. W. Larsson
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2674)


This paper presents a novel method for segmentation of cardiac perfusion MRI. By performing complex analyses of variance and clustering in an annotated training set off-line, the presented method provides real-time segmentation in an on-line setting. This renders the method feasible for e.g. analysis of large image databases or for live non-rigid motion-compensation in modern MR scanners. Changes in image intensity during the bolus passage is modelled by an Active Appearance Model augmented with a cluster analysis of the training set and priors on pose and shape. Preliminary validation of the method is carried out using 250 MR perfusion images, acquired without breath-hold from five subjects. Quantitative and qualitative results show high accuracy, given the limited number of subjects.


Myocardial Perfusion Myocardial Perfusion Imaging Right Ventricle Segmentation Result Active Appearance Model 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Mikkel B. Stegmann
    • 1
    • 2
  • Henrik B. W. Larsson
    • 2
    • 3
  1. 1.Informatics and Mathematical ModellingTechnical University of DenmarkDenmark
  2. 2.Danish Research Centre for Magnetic ResonanceH:S Hvidovre HospitalDenmark
  3. 3.MR-Senteret, St. Olavs HospitalTrondheim UniversityNorway

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