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

Mikkel B. Stegmann, Henrik B. W. Larsson

AbstractThis 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.
Keywordssegmentation, myocardial perfusion imaging, active appearance models, clustering
TypeConference paper [With referee]
ConferenceFunctional Imaging and Modeling of the Heart, FIMH 2003
EditorsMagnin, I. E., Montagnat, J., Clarysse, P., Nenonen, J., Katila, T.
Year2003    Month June    Vol. 2674    pp. 151-161
PublisherSpringer Verlag
AddressLyon, France
SeriesLecture Notes in Computer Science
Electronic version(s)[pdf]
BibTeX data [bibtex]
IMM Group(s)Image Analysis & Computer Graphics