Journal of Medical Systems

, 40:243 | Cite as

Processing Time Reduction: an Application in Living Human High-Resolution Diffusion Magnetic Resonance Imaging Data

  • Nicolás F . Lori
  • Augustin Ibañez
  • Rui Lavrador
  • Lucia Fonseca
  • Carlos Santos
  • Rui Travasso
  • Artur Pereira
  • Rosaldo Rossetti
  • Nuno Sousa
  • Victor Alves
Systems-Level Quality Improvement
Part of the following topical collections:
  1. Health Information Systems & Technologies

Abstract

High Angular Resolution Diffusion Imaging (HARDI) is a type of brain imaging that collects a very large amount of data, and if many subjects are considered then it amounts to a big data framework (e.g., the human connectome project has 20 Terabytes of data). HARDI is also becoming increasingly relevant for clinical settings (e.g., detecting early cerebral ischemic changes in acute stroke, and in pre-clinical assessment of white matter-WM anatomy using tractography). Thus, this method is becoming a routine assessment in clinical settings. In such settings, the computation time is critical, and finding forms of reducing the processing time in high computation processes such as Diffusion Spectrum Imaging (DSI), a form of HARDI data, is very relevant to increase data-processing speed. Here we analyze a method for reducing the computation time of the dMRI-based axonal orientation distribution function h by using Monte Carlo sampling-based methods for voxel selection. Results evidenced a robust reduction in required data sampling of about 50 % without losing signal’s quality. Moreover, we show that the convergence to the correct value in this type of Monte Carlo HARDI/DSI data-processing has a linear improvement in data-processing speed of the ODF determination. Although further improvements are needed, our results represent a promissory step for future processing time reduction in big data.

Keywords

White matter Diffusion MRI Monte Carlo sampling methods Optimization Axonal ODF 

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Nicolás F . Lori
    • 1
    • 2
    • 3
    • 4
    • 5
  • Augustin Ibañez
    • 5
    • 6
    • 7
    • 8
    • 9
  • Rui Lavrador
    • 3
  • Lucia Fonseca
    • 10
    • 11
    • 12
  • Carlos Santos
    • 3
  • Rui Travasso
    • 3
    • 10
  • Artur Pereira
    • 13
  • Rosaldo Rossetti
    • 14
  • Nuno Sousa
    • 15
  • Victor Alves
    • 1
  1. 1.Algoritmi CentreUniversity of MinhoBragaPortugal
  2. 2.Laboratory of Neuroimaging and Neuroscience (LANEN), Institute of Translational and Cognitive Neuroscience (INCyT), INECO Foundation RosarioFavaloro UniversityRosarioArgentina
  3. 3.Institute for Biomedical Imaging and Life Sciences (IBILI), Faculty of MedicineUniversity of CoimbraCoimbraPortugal
  4. 4.INECO Neurociencias OroñoRosarioArgentina
  5. 5.Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Translational and Cognitive Neuroscience (INCyT), INECO FoundationFavaloro UniversityBuenos AiresArgentina
  6. 6.National Scientific and Technical Research Council (CONICET)Buenos AiresArgentina
  7. 7.Universidad Autónoma del CaribeBarranquillaColombia
  8. 8.Department of PsychologyUniversidad Adolfo IbáñezSantiagoChile
  9. 9.Centre of Excellence in Cognition and its DisordersAustralian Research Council (ACR)SydneyAustralia
  10. 10.Center for Physics Computation (CFC), Faculty of Science and TechnologyUniversity of CoimbraCoimbraPortugal
  11. 11.Maastricht UniversityMaastrichtNetherlands
  12. 12.Eindhoven University of TechnologyEindhovenNetherlands
  13. 13.IETTAUniversity of AveiroAveiroPortugal
  14. 14.LIACUniversity of PortoPortoPortugal
  15. 15.3B’sUniversity of MinhoBragaPortugal

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