Motion-compensation of Cardiac Perfusion MRI using a Statistical Texture Ensemble

Mikkel Bille Stegmann, Henrik B. W. Larsson

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    Abstract

    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 provide real-time segmentation in an on-line setting. This renders the method feasible for e.g. analysis of large image databases or for live motion-compensation in modern MR scanners.
    Changes in image intensity during the bolus passage is modelled by an Active Appearance Model is 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. Results show high accuracy, given the limited number of subjects.
    Original languageEnglish
    Title of host publicationFunctional Imaging and Modeling of the Heart, FIMH 2003
    PublisherSpringer Verlag
    Publication date2003
    Pages151-161
    DOIs
    Publication statusPublished - 2003
    EventFunctional Imaging and Modeling of the Heart, FIMH 2003 -
    Duration: 1 Jan 2003 → …

    Conference

    ConferenceFunctional Imaging and Modeling of the Heart, FIMH 2003
    Period01/01/2003 → …
    SeriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume2674
    ISSN0302-9743

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