A deconvolution approach based on multi-tensor model to solve fiber crossing in diffusion-MRI

F. Dell'Acqua, G. Rizzo, P. Scifo, R. A. Clarke, G. Scotti, S. Cerutti, F. Fazio

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A deconvolution approach, based on a multi-tensor model, is presented to solve fiber crossing in diffusion MRI. In order to provide a direct physical interpretation of the signal generation process, we re-wrote the classical multi-tensor model, identifying a significant scalar parameter a to characterize the deconvolution process. Simulations show that, in presence of noise, the method is able to correctly separate fiber crossing. Application on in-vivo data highlights the ability of our approach to distinguish more than two fibers within the same voxel, suggesting its application in fiber tracking or connectivity studies even of complex brain structures.

Original languageEnglish
Title of host publicationAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Pages1415-1418
Number of pages4
Volume7 VOLS
Publication statusPublished - 2005
Event2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 - Shanghai, China
Duration: Sep 1 2005Sep 4 2005

Other

Other2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
CountryChina
CityShanghai
Period9/1/059/4/05

ASJC Scopus subject areas

  • Bioengineering

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    Dell'Acqua, F., Rizzo, G., Scifo, P., Clarke, R. A., Scotti, G., Cerutti, S., & Fazio, F. (2005). A deconvolution approach based on multi-tensor model to solve fiber crossing in diffusion-MRI. In Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings (Vol. 7 VOLS, pp. 1415-1418). [1616695]