Published May 2019 | Version v1
Journal article

Reducing the number of samples in spatiotemporal dMRI acquisition design

  • 1. Univ Cote Azur, Inria Sophia Antipolis Mediterranee, Valbonne (France)
  • 2. CENIR Ctr NeuroImaging Res, ICM Brain and Spine Inst, Paris (France)
  • 3. Univ Paris Saclay, CEA, INRIA, St Aubin (France)

Description

Purpose: Acquisition time is a major limitation in recovering brain white matter microstructure with diffusion magnetic resonance imaging. The aim of this paper is to bridge the gap between growing demands on spatiotemporal resolution of diffusion signal and the real-world time limitations. The authors introduce an acquisition scheme that reduces the number of samples under adjustable quality loss. Methods: Finding a sampling scheme that maximizes signal quality and satisfies given time constraints is NP-hard. Therefore, a heuristic method based on genetic algorithm is proposed in order to find suboptimal solutions in acceptable time. The analyzed diffusion signal representation is defined in the q tau space, so that it captures both spatial and temporal phenomena. Results: The experiments on synthetic data and in vivo diffusion images of the C57B16 wild-type mouse corpus callosum reveal superiority of the proposed approach over random sampling and even distribution in the q tau space. Conclusions: The use of genetic algorithm allows to find acquisition parameters that guarantee high signal reconstruction accuracy under given time constraints. In practice, the proposed approach helps to accelerate the acquisition for the use of q tau-dMRI signal representation. (authors)

Availability note (English)

Available from doi: http://dx.doi.org/10.1002/mrm.27601

Additional details

Identifiers

Publishing Information

Journal Title
Magnetic Resonance in Medicine
Journal Volume
81
Journal Issue
no.5
Journal Page Range
p. 3218-3233
ISSN
0740-3194

INIS

Country of Publication
United States
Country of Input or Organization
France
INIS RN
52086515
Subject category
S62: RADIOLOGY AND NUCLEAR MEDICINE;
Descriptors DEI
ACCURACY; BRAIN; GENETIC ALGORITHMS; GENETICS; IN VIVO; MICE; NMR IMAGING; SAMPLING
Descriptors DEC
ALGORITHMS; ANIMALS; BIOLOGY; BODY; CENTRAL NERVOUS SYSTEM; DIAGNOSTIC TECHNIQUES; MAMMALS; MATHEMATICAL LOGIC; NERVOUS SYSTEM; ORGANS; RODENTS; VERTEBRATES