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@ARTICLE{Tang:202294,
      author       = {Tang, Yunqing and Dai, Luru and Zhang, Xiaoming and Li,
                      Junbai and Hendriks, Johnny and Fan, Xiaoming and Gruteser,
                      Nadine and Meisenberg, Annika and Baumann, A. and
                      Katranidis, Alexandros and Gensch, Thomas},
      title        = {{SNSMIL}, a real-time single molecule identification and
                      localization algorithm for super-resolution fluorescence
                      microscopy},
      journal      = {Scientific reports},
      volume       = {5},
      issn         = {2045-2322},
      address      = {London},
      publisher    = {Nature Publishing Group},
      reportid     = {FZJ-2015-04565},
      pages        = {11073 -},
      year         = {2015},
      abstract     = {Single molecule localization based super-resolution
                      fluorescence microscopy offers significantly higher spatial
                      resolution than predicted by Abbe’s resolution limit for
                      far field optical microscopy. Such super-resolution images
                      are reconstructed from wide-field or total internal
                      reflection single molecule fluorescence recordings.
                      Discrimination between emission of single fluorescent
                      molecules and background noise fluctuations remains a great
                      challenge in current data analysis. Here we present a
                      real-time, and robust single molecule identification and
                      localization algorithm, SNSMIL (Shot Noise based Single
                      Molecule Identification and Localization). This algorithm is
                      based on the intrinsic nature of noise, i.e., its Poisson or
                      shot noise characteristics and a new identification
                      criterion, QSNSMIL, is defined. SNSMIL improves the
                      identification accuracy of single fluorescent molecules in
                      experimental or simulated datasets with high and
                      inhomogeneous background. The implementation of SNSMIL
                      relies on a graphics processing unit (GPU), making real-time
                      analysis feasible as shown for real experimental and
                      simulated datasets.},
      cin          = {ICS-4 / ICS-5},
      ddc          = {000},
      cid          = {I:(DE-Juel1)ICS-4-20110106 / I:(DE-Juel1)ICS-5-20110106},
      pnm          = {552 - Engineering Cell Function (POF3-552)},
      pid          = {G:(DE-HGF)POF3-552},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000356584200001},
      pubmed       = {pmid:26098742},
      doi          = {10.1038/srep11073},
      url          = {https://juser.fz-juelich.de/record/202294},
}