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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},
}