In this paper we present the research performed on functional Magnetic Resonance Imaging reconstruction (fMRI). In this kind of application in the medical area, undersampled sets of data are acquired in the frequency-phase space at successive time instants. The Fourier techniques produce images of low quality. Hence, some different image reconstruction methods are considered: the Keyhole method and the RIGR (Reduced--encoding Imaging by Generalized Series Reconstruction) method with one or two reference images. The solution of the ill-posed linear systems coming from the RIGR method is carefully considered; some regularization methods suitable for hermitian positive semidefinite matrices are analysed and tested. We have realized a Matlab tool with graphical interface that implements the described reconstruction methods on fMRI sequences from real acquisitions. Some examples of reconstructed images obtained with the toolbox are presented.

Numerical methods and software for functional magnetic resonance images reconstruction

ZANGHIRATI, Gaetano
2000

Abstract

In this paper we present the research performed on functional Magnetic Resonance Imaging reconstruction (fMRI). In this kind of application in the medical area, undersampled sets of data are acquired in the frequency-phase space at successive time instants. The Fourier techniques produce images of low quality. Hence, some different image reconstruction methods are considered: the Keyhole method and the RIGR (Reduced--encoding Imaging by Generalized Series Reconstruction) method with one or two reference images. The solution of the ill-posed linear systems coming from the RIGR method is carefully considered; some regularization methods suitable for hermitian positive semidefinite matrices are analysed and tested. We have realized a Matlab tool with graphical interface that implements the described reconstruction methods on fMRI sequences from real acquisitions. Some examples of reconstructed images obtained with the toolbox are presented.
Formiconi, A. R.; LOLI PICCOLOMINI, E.; Martini, S.; Zama, F.; Zanghirati, Gaetano
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11392/1211193
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