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Proceedings Paper

Segmentation of cardiac MR and CT image sequences using model-based registration of a 4D statistical model
Author(s): Dimitrios Perperidis; Raad Mohiaddin; Philip Edwards; Daniel Rueckert
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Paper Abstract

In this paper we present a novel approach to the problem of fitting a 4D statistical shape model of the myocardium to cardiac MR and CT image sequences. The 4D statistical model has been constructed from 25 cardiac MR image sequences from normal volunteers. The model is controlled by two sets of shape parameters. The first set of shape parameters describes shape changes due to inter-subject variability while the second set of shape parameters describes shape changes due to intra-subject variability, i.e. the cardiac contraction and relaxation. A novel fitting approach is used to estimate the optimal parameters of the cardiac shape model. The fitting of the model is performed simultaneously for the entire image sequences. The method has been tested on 5 cardiac MR image sequences. Furthermore, we have also tested the method using a cardiac CT image sequence. The result demonstrate that the method is not only able to fit the 4D model to cardiac MR image sequences, but also to cardiac image sequences from a different modality (CT).

Paper Details

Date Published: 26 March 2007
PDF: 9 pages
Proc. SPIE 6512, Medical Imaging 2007: Image Processing, 65121D (26 March 2007); doi: 10.1117/12.706778
Show Author Affiliations
Dimitrios Perperidis, Imperial College London (United Kingdom)
Raad Mohiaddin, Royal Brompton Hospital (United Kingdom)
Philip Edwards, Imperial College London, St. Mary's Hospital (United Kingdom)
Daniel Rueckert, Imperial College London (United Kingdom)

Published in SPIE Proceedings Vol. 6512:
Medical Imaging 2007: Image Processing
Josien P. W. Pluim; Joseph M. Reinhardt, Editor(s)

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