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A Novel Multiparametric Approach to 3D Quantitative MRI of the Brain
Author(s) -
Giuseppe Palma,
Enrico Tedeschi,
Pasquale Borrelli,
Sirio Cocozza,
Carmela Russo,
Saifeng Liu,
Yongquan Ye,
Marco Comerci,
Bruno Alfano,
Marco Salvatore,
E. Mark Haacke,
Marcello Mancini
Publication year - 2015
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0134963
Subject(s) - physics , measure (data warehouse) , communication noise , nuclear magnetic resonance , noise (video) , signal (programming language) , magnetic resonance imaging , relaxation (psychology) , radio frequency , statistical physics , computational physics , set (abstract data type) , signal to noise ratio (imaging) , computer science , artificial intelligence , image (mathematics) , data mining , optics , neuroscience , telecommunications , biology , medicine , linguistics , philosophy , radiology , programming language
Magnetic Resonance properties of tissues can be quantified in several respects: relaxation processes, density of imaged nuclei, magnetism of environmental molecules, etc. In this paper, we propose a new comprehensive approach to obtain 3D high resolution quantitative maps of arbitrary body districts, mainly focusing on the brain. The theory presented makes it possible to map longitudinal ( R 1 ), pure transverse ( R 2 ) and free induction decay (R 2 *) rates, along with proton density (PD) and magnetic susceptibility ( χ ), from a set of fast acquisition sequences in steady-state that are highly insensitive to flow phenomena. A novel denoising scheme is described and applied to the acquired datasets to enhance the signal to noise ratio of the derived maps and an information theory approach compensates for biases from radio frequency (RF) inhomogeneities, if no direct measure of the RF field is available. Finally, the results obtained on sample brain scans of healthy controls and multiple sclerosis patients are presented and discussed.

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