Title
Multi-voxel algorithm for quantitative bi-exponential MRI <tex>$T_{1}$</tex> estimation Multi-voxel algorithm for quantitative bi-exponential MRI <tex>$T_{1}$</tex> estimation
Author
Faculty/Department
Faculty of Sciences. Physics
Publication type
article
Publication
Bellingham :Spie-int soc optical engineering ,
Subject
Physics
Computer. Automation
Source (journal)
Proceedings of SPIE
Volume/pages
9784(2016) , 14 p.
ISSN
0277-786X
Article Reference
978402
ISBN
978-1-5106-0019-5
ISI
000382313300001
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
Quantification of the spin-lattice relaxation time, T1, of tissues is important for characterization of tissues in clinical magnetic resonance imaging (MRI). In T1 mapping, T1 values are estimated from a set of T1-weighted MRI images. Due to the limited spatial resolution of the T1-weighted images, one voxel might consist of two tissues, causing partial volume effects (PVE). In conventional mono-exponential T1 estimation, these PVE result in systematic errors in the T1 map. To account for PVE, single-voxel bi-exponential estimators have been suggested. Unfortunately, in general, they suffer from low accuracy and precision. In this work, we propose a joint multi-voxel bi-exponential T1 estimator (JMBE) and compare its performance to a single-voxel bi-exponential T1 estimator (SBE). Results show that, in contrast to the SBE, and for clinically achievable single-voxel SNRs, the JMBE is accurate and efficient if four or more neighboring voxels are used in the joint estimation framework. This illustrates that, for clinically realistic SNRs, accurate results for quantitative biexponential T1 estimation are only achievable if information of neighboring voxels is incorporated.
Handle