Motion-compensation of Cardiac Perfusion MRI using a Statistical Texture Ensemble | Mikkel B. Stegmann, Henrik B. W. Larsson
| | 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. | | Keywords | segmentation, myocardial perfusion imaging, active appearance models, clustering | | Type | Conference paper [With referee] | | Conference | Functional Imaging and Modeling of the Heart, FIMH 2003 | | Editors | Magnin, I. E., Montagnat, J., Clarysse, P., Nenonen, J., Katila, T. | | Year | 2003 Month June Vol. 2674 pp. 151-161 | | Publisher | Springer Verlag | | Address | Lyon, France | | Series | Lecture Notes in Computer Science | | Electronic version(s) | [pdf] | | BibTeX data | [bibtex] | | IMM Group(s) | Image Analysis & Computer Graphics |
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