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International Conference on Medical Image Computing and Computer-Assisted Intervention

MICCAI 2019: Computational Diffusion MRI pp 69–76Cite as

Tissue Segmentation Using Sparse Non-negative Matrix Factorization of Spherical Mean Diffusion MRI Data

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Part of the book series: Mathematics and Visualization ((MATHVISUAL))

Abstract

In this paper, we present a method based on sparse non-negative matrix factorization (NMF) for brain tissue segmentation using diffusion MRI (DMRI) data. Unlike existing NMF-based approaches, in our method NMF is applied to the spherical mean data, computed on a per-shell basis, instead of the original diffusion-weighted images. This is motivated by the fact that the spherical mean is independent of the fiber orientation distribution and is only dependent on tissue microstructure. Applying NMF to the spherical mean data will hence allow tissue signal separation based solely on the microstructural properties, unconfounded by factors such as fiber dispersion and crossing. We show results explaining why applying NMF directly on the diffusion-weighted images fails and why our method is able to yield the expected outcome, producing tissue segmentation with greater accuracy.

This work was supported in part by NIH grants (NS093842, EB022880, EB006733, EB009634, AG041721, MH100217, and AA012388) and NSFC grants (11671022 and 61502392).

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Author information

Authors and Affiliations

  1. Department of Radiology and BRIC, University of North Carolina, Chapel Hill, NC, USA

    Peng Sun, Ye Wu, Geng Chen, Dinggang Shen & Pew-Thian Yap

  2. School of Computer Science, Northwestern Polytechnical University, Xi An, China

    Peng Sun

  3. Institute of Information Processing and Automation, Zhejiang University of Technology, Hangzhou, China

    Ye Wu

  4. School of Electronics and Information, Northwestern Polytechnical University, Xi An, China

    Jun Wu

Authors
  1. Peng Sun
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  2. Ye Wu
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  3. Geng Chen
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  4. Jun Wu
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  5. Dinggang Shen
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  6. Pew-Thian Yap
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Corresponding author

Correspondence to Pew-Thian Yap .

Editor information

Editors and Affiliations

  1. Centre for Medical Image Computing, University College London, London, UK

    Elisenda Bonet-Carne

  2. Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK

    Francesco Grussu

  3. Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Lipeng Ning

  4. Laboratory of Neuro Imaging (LONI), Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA

    Farshid Sepehrband

  5. Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, UK

    Chantal M. W. Tax

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Sun, P., Wu, Y., Chen, G., Wu, J., Shen, D., Yap, PT. (2019). Tissue Segmentation Using Sparse Non-negative Matrix Factorization of Spherical Mean Diffusion MRI Data. In: Bonet-Carne, E., Grussu, F., Ning, L., Sepehrband, F., Tax, C. (eds) Computational Diffusion MRI. MICCAI 2019. Mathematics and Visualization. Springer, Cham. https://doi.org/10.1007/978-3-030-05831-9_6

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