Optimal Diffusion Tensor Imaging with Repeated Measurements
Paper i proceeding, 2013

Several data acquisition schemes for diffusion MRI have been proposed and explored to date for the reconstruction of the 2nd order tensor. Our main contributions in this paper are: (i) the definition of a new class of sampling schemes based on repeated measurements in every sampling point; (ii) two novel schemes belonging to this class; and (iii) a new reconstruction framework for the second scheme. We also present an evaluation, based on Monte Carlo computer simulations, of the performances of these schemes relative to known optimal sampling schemes for both 2nd and 4th order tensors. The results demonstrate that tensor estimation by the proposed sampling schemes and estimation framework is more accurate and robust.

optimal sampling scheme

diffusion tensor imaging

tensor estimation

Författare

Mohammad Alipoor

Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

Irene Yu-Hua Gu

Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

Andrew Mehnert

Signaler och system, Signalbehandling och medicinsk teknik, Digitala bildsystem och bildanalys

Y Lilja

Göteborgs universitet

Daniel Nilsson

Göteborgs universitet

Lecture Notes in Computer Science

0302-9743 (ISSN)

Vol. 8149 687-694

Styrkeområden

Livsvetenskaper och teknik

Ämneskategorier

Systemvetenskap

Neurologi

Datorseende och robotik (autonoma system)

Medicinsk bildbehandling

DOI

10.1007/978-3-642-40811-3_86

ISBN

978-3-642-40810-6