Spatio-Temporal dMRI Acquisition Design: Reducing the Number of Samples Through a Relaxed Probabilistic Model

  • Patryk Filipiak
  • Rutger Fick
  • Alexandra Petiet
  • Mathieu Santin
  • Anne-Charlotte Philippe
  • Stephane Lehericy
  • Rachid Deriche
  • Demian Wassermann
Conference paper
Part of the Mathematics and Visualization book series (MATHVISUAL)

Abstract

Acquisition time is a major limitation in recovering brain white matter microstructure with diffusion Magnetic Resonance Imaging. Finding a sampling scheme that maximizes signal quality and satisfies given time constraints is NP-hard. We alleviate that by introducing a relaxed probabilistic model of the problem, for which sub-optimal solutions can be found effectively. Our model is defined in the space, so that it captures both spacial and temporal phenomena. The experiments on synthetic data and in-vivo diffusion images of the C57Bl6 wild-type mice reveal superiority of our technique over random sampling and even distribution in the space.

Notes

Acknowledgements

This work has received funding from the ANR/NSF award NeuroRef; the European Research Council (ERC) under the Horizon 2020 research and innovation program (ERC Advanced Grant agreement No 694665 : CoBCoM); the MAXIMS grant funded by ICM’s The Big Brain Theory Program and ANR-10-IAIHU-06.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Patryk Filipiak
    • 1
  • Rutger Fick
    • 1
  • Alexandra Petiet
    • 2
  • Mathieu Santin
    • 2
  • Anne-Charlotte Philippe
    • 2
  • Stephane Lehericy
    • 2
  • Rachid Deriche
    • 1
  • Demian Wassermann
    • 1
  1. 1.Université Côte d’Azur - Inria Sophia Antipolis-MéditerranéeValbonneFrance
  2. 2.CENIR - Center for NeuroImaging ResearchICM - Brain and Spine InstituteParisFrance

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