High density molecule localization for super-resolution microscopy using CEL0 based sparse approximation

Simon Gazagnes 1, 2 Emmanuel Soubies 1, 3 Laure Blanc-Féraud 1, 3
1 MORPHEME - Morphologie et Images
CRISAM - Inria Sophia Antipolis - Méditerranée , IBV - Institut de Biologie Valrose : U1091, SIS - Signal, Images et Systèmes
Abstract : Single molecule localization microscopy has made great improvements in spatial resolution achieving performance beyond the diffraction limit by sequentially activating and imaging small subsets of molecules. Here, we present an algorithm designed for high-density molecule localization which is of a major importance in order to improve the temporal resolution of such microscopy techniques. We formulate the localization problem as a sparse approximation problem which is then relaxed using the recently proposed CEL0 penalty, allowing an optimization through recent nonsmooth nonconvex algorithms. Finally, performances of the proposed method are compared with one of the best current method for high-density molecules localization on simulated and real data.
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Communication dans un congrès
ISBI 2017 - IEEE International Symposium on Biomedical Imaging, Apr 2017, Melbourne, Australia. pp.4, Proceedings of ISBI 2017
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Contributeur : Emmanuel Soubies <>
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Dernière modification le : vendredi 16 juin 2017 - 01:11:58
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Simon Gazagnes, Emmanuel Soubies, Laure Blanc-Féraud. High density molecule localization for super-resolution microscopy using CEL0 based sparse approximation. ISBI 2017 - IEEE International Symposium on Biomedical Imaging, Apr 2017, Melbourne, Australia. pp.4, Proceedings of ISBI 2017. <hal-01443565>

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