Super-resolution fluorescence microscopy overcomes blurring arising from light diffraction, allowing the reconstruction of fine scale details in biological structures. Standard methods come at the expense of long acquisition time and/or harmful effects on the biological sample, which makes the problem quite challenging for the imaging of body cells. A promising new avenue is the exploitation of molecules fluctuations, allowing live-cell imaging with good spatio-temporal resolution through common microscopes and conventional fluorescent dyes. Several numerical algorithms have been developed in the literature and used for fluctuant time series. These techniques are developed within the discrete setting, namely the super-resolved image is defined on a finer grid than the observed images. On the contrary, gridless optimisation does not rely on a fine grid and is rather an optimisation of Dirac measures in number, amplitudes and positions. In this work, we present a gridless problem accounting for the independence of fluctuations.
机构:
Columbia Univ, Dept Chem, New York, NY 10027 USA
Columbia Univ, Kavli Inst Brain Sci, New York, NY 10027 USAColumbia Univ, Dept Chem, New York, NY 10027 USA
Zhao, Zhilun
Min, Wei
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Columbia Univ, Dept Chem, New York, NY 10027 USA
Columbia Univ, Kavli Inst Brain Sci, New York, NY 10027 USA
Columbia Univ, Dept Biomed Engn, New York, NY 10027 USAColumbia Univ, Dept Chem, New York, NY 10027 USA
机构:
Harvard Univ, Howard Hughes Med Inst, Cambridge, MA 02138 USA
Harvard Univ, Dept Chem & Biol Chem, Cambridge, MA 02138 USAHarvard Univ, Howard Hughes Med Inst, Cambridge, MA 02138 USA
Huang, Bo
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机构:
Bates, Mark
Zhuang, Xiaowei
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机构:
Harvard Univ, Howard Hughes Med Inst, Cambridge, MA 02138 USA
Harvard Univ, Dept Chem & Biol Chem, Cambridge, MA 02138 USA
Harvard Univ, Dept Phys, Cambridge, MA 02138 USAHarvard Univ, Howard Hughes Med Inst, Cambridge, MA 02138 USA