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@ARTICLE{Dammers:7896,
      author       = {Dammers, J. and Axer, M. and Gräßel, D. and Palm, C. and
                      Zilles, K. and Amunts, K. and Pietrzyk, U.},
      title        = {{S}ignal enhancement in polarized light imaging by means of
                      independent component analysis},
      journal      = {NeuroImage},
      volume       = {49},
      issn         = {1053-8119},
      address      = {Orlando, Fla.},
      publisher    = {Academic Press},
      reportid     = {PreJuSER-7896},
      pages        = {1241 - 1248},
      year         = {2010},
      note         = {This work was supported by the Initiative and Networking
                      Fund of the Helmholtz Association within the Helmholtz
                      Alliance on Systems Biology. Moreover, we like to thank Dr.
                      Bernd Sellhaus, MD (Institute of Neuropathology, RWTH Aachen
                      University, Germany). We are grateful to Markus Cremer
                      (Institute of Neuroscience and Medicine, Research Centre
                      Julich, Germany) for excellent technical assistance and the
                      preparation of the histological sections. Mechanical
                      assembly of the polarimeter was done by the workshop of
                      Friedrich-Schiller University of Jena, Germany.},
      abstract     = {Polarized light imaging (PLI) enables the evaluation of
                      fiber orientations in histological sections of human
                      postmortem brains, with ultra-high spatial resolution. PLI
                      is based on the birefringent properties of the myelin sheath
                      of nerve fibers. As a result, the polarization state of
                      light propagating through a rotating polarimeter is changed
                      in such a way that the detected signal at each measurement
                      unit of a charged-coupled device (CCD) camera describes a
                      sinusoidal signal. Vectors of the fiber orientation defined
                      by inclination and direction angles can then directly be
                      derived from the optical signals employing PLI analysis.
                      However, noise, light scatter and filter inhomogeneities
                      interfere with the original sinusoidal PLI signals. We here
                      introduce a novel method using independent component
                      analysis (ICA) to decompose the PLI images into
                      statistically independent component maps. After
                      decomposition, gray and white matter structures can clearly
                      be distinguished from noise and other artifacts. The signal
                      enhancement after artifact rejection is quantitatively
                      evaluated in 134 histological whole brain sections. Thus,
                      the primary sinusoidal signals from polarized light imaging
                      can be effectively restored after noise and artifact
                      rejection utilizing ICA. Our method therefore contributes to
                      the analysis of nerve fiber orientation in the human brain
                      within a micrometer scale.},
      keywords     = {Artifacts / Brain: ultrastructure / Calibration / Dust /
                      Humans / Image Enhancement: methods / Image Processing,
                      Computer-Assisted: methods / Light / Myelin Sheath:
                      ultrastructure / Nerve Fibers, Myelinated: ultrastructure /
                      Nerve Fibers, Unmyelinated: ultrastructure / Optics and
                      Photonics: methods / Dust (NLM Chemicals) / J (WoSType)},
      cin          = {INM-1 / INM-2 / JARA-BRAIN},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-1-20090406 / I:(DE-Juel1)INM-2-20090406 /
                      $I:(DE-82)080010_20140620$},
      pnm          = {Funktion und Dysfunktion des Nervensystems (FUEK409) /
                      89574 - Theory, modelling and simulation (POF2-89574)},
      pid          = {G:(DE-Juel1)FUEK409 / G:(DE-HGF)POF2-89574},
      shelfmark    = {Neurosciences / Neuroimaging / Radiology, Nuclear Medicine
                      $\&$ Medical Imaging},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:19733674},
      UT           = {WOS:000272808400011},
      doi          = {10.1016/j.neuroimage.2009.08.059},
      url          = {https://juser.fz-juelich.de/record/7896},
}