A deconvolution approach is presented to solve fiber crossing in diffusion magnetic resonance imaging. In order to provide a direct physical interpretation of the signal generation process, we started from the classical multicompartment model and rewrote this in terms of a convolution process, identifying a significant scalar parameter alpha to characterize the physical system response. Deconvolution is performed by a modified version of the Richardson-Lucy algorithm. Simulations show the ability of this method to correctly separate fiber crossing, even in the presence of noisy data, with lower signal-to-noise ratio, and imprecision in the impulse response function imposed during deconvolution. The in vivo data confirms the efficacy of this method to resolve fiber crossing in real complex brain structures. These results suggest the usefulness of our approach in fiber tracking or connectivity studies.

Dell'Acqua, F., Rizzo, G., Scifo, P., Clarke, R., Scotti, G., Fazio, F. (2007). A model-based deconvolution approach to solve fiber crossing in diffusion-weighted MR imaging. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 54(3), 462-472 [10.1109/TBME.2006.888830].

A model-based deconvolution approach to solve fiber crossing in diffusion-weighted MR imaging

FAZIO, FERRUCCIO
2007

Abstract

A deconvolution approach is presented to solve fiber crossing in diffusion magnetic resonance imaging. In order to provide a direct physical interpretation of the signal generation process, we started from the classical multicompartment model and rewrote this in terms of a convolution process, identifying a significant scalar parameter alpha to characterize the physical system response. Deconvolution is performed by a modified version of the Richardson-Lucy algorithm. Simulations show the ability of this method to correctly separate fiber crossing, even in the presence of noisy data, with lower signal-to-noise ratio, and imprecision in the impulse response function imposed during deconvolution. The in vivo data confirms the efficacy of this method to resolve fiber crossing in real complex brain structures. These results suggest the usefulness of our approach in fiber tracking or connectivity studies.
Articolo in rivista - Articolo scientifico
DTI, DW-MRI, HARDI, Richardson-Lucy algorithm, fiber crossing, multicompartment model, spherical deconvolution
English
2007
54
3
462
472
15
none
Dell'Acqua, F., Rizzo, G., Scifo, P., Clarke, R., Scotti, G., Fazio, F. (2007). A model-based deconvolution approach to solve fiber crossing in diffusion-weighted MR imaging. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 54(3), 462-472 [10.1109/TBME.2006.888830].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/26384
Citazioni
  • Scopus 160
  • ???jsp.display-item.citation.isi??? 147
Social impact