ARMA regularization of cardiac perfusion modeling

Author

Batchelor, Philip ; Chiribiri, Amedeo ; Nooralipour, Niloufar Zarinabad ; Cvetkovic, Zoran

Author_Institution

Div. of Imaging Sci., King´´s Coll. London, London, UK

fYear

2010

fDate

14-19 March 2010

Firstpage

642

Lastpage

645

Abstract

Cardiac perfusion modelling using ARMA systems is studied. ARMA is a generalization of a recently proposed exponential approximation technique, which was shown to exhibit better performance than the widely used truncated singular value decomposition method. Experiments demonstrate that ARMA achieves results as accurate as the those obtained using the exponential approximation, but it its at the same time less sensitive to additive noise and model order selection.

Keywords

biomedical MRI; cardiology; haemorheology; medical image processing; physiological models; singular value decomposition; ARMA regularization; additive noise; cardiac perfusion modeling; exponential approximation technique; model order selection; truncated singular value decomposition; Additive noise; Blood flow; Convolution; Deconvolution; Educational institutions; Fluid flow measurement; Magnetic resonance imaging; Myocardium; Noise robustness; Singular value decomposition; ARMA; Cardiac perfusion; exponential approximation; robustness;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on

Conference_Location

Dallas, TX

ISSN

1520-6149

Print_ISBN

978-1-4244-4295-9

Electronic_ISBN

1520-6149

Type

conf

DOI

10.1109/ICASSP.2010.5495154

Filename

5495154