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Proceedings Paper

Bi-temporal 3D active appearance models with applications to unsupervised ejection fraction estimation
Author(s): Mikkel B. Stegmann; Dorthe Pedersen
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Paper Abstract

Rapid and unsupervised quantitative analysis is of utmost importance to ensure clinical acceptance of many examinations using cardiac magnetic resonance imaging (MRI). We present a framework that aims at fulfilling these goals for the application of left ventricular ejection fraction estimation in four-dimensional MRI. The theoretical foundation of our work is the generative two-dimensional Active Appearance Models by Cootes et al., here extended to bi-temporal, three-dimensional models. Further issues treated include correction of respiratory induced slice displacements, systole detection, and a texture model pruning strategy. Cross-validation carried out on clinical-quality scans of twelve volunteers indicates that ejection fraction and cardiac blood pool volumes can be estimated automatically and rapidly with accuracy on par with typical inter-observer variability.

Paper Details

Date Published: 29 April 2005
PDF: 15 pages
Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); doi: 10.1117/12.594930
Show Author Affiliations
Mikkel B. Stegmann, Technical Univ. of Denmark (Denmark)
Copenhagen Univ. Hospital Hvidovre (Denmark)
Dorthe Pedersen, Copenhagen Univ. Hospital Hvidovre (Denmark)


Published in SPIE Proceedings Vol. 5747:
Medical Imaging 2005: Image Processing
J. Michael Fitzpatrick; Joseph M. Reinhardt, Editor(s)

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