Title: Sparse deconvolution of high-density super-resolution images
Authors: Hugelier, Siewert
de Rooi, Johan J
Bernex, Romain
Duwé, Sam
Devos, Olivier
Sliwa, Michel
Dedecker, Peter
Eilers, Paul H C
Ruckebusch, Cyril # ×
Issue Date: Feb-2016
Series Title: Scientific Reports vol:6 pages:21413
Article number: 10.1038/srep21413
Abstract: In wide-field super-resolution microscopy, investigating the nanoscale structure of cellular processes, and resolving fast dynamics and morphological changes in cells requires algorithms capable of working with a high-density of emissive fluorophores. Current deconvolution algorithms estimate fluorophore density by using representations of the signal that promote sparsity of the super-resolution images via an L1-norm penalty. This penalty imposes a restriction on the sum of absolute values of the estimates of emitter brightness. By implementing an L0-norm penalty - on the number of fluorophores rather than on their overall brightness - we present a penalized regression approach that can work at high-density and allows fast super-resolution imaging. We validated our approach on simulated images with densities up to 15 emitters per μm(-2) and investigated total internal reflection fluorescence (TIRF) data of mitochondria in a HEK293-T cell labeled with DAKAP-Dronpa. We demonstrated super-resolution imaging of the dynamics with a resolution down to 55 nm and a 0.5 s time sampling.
ISSN: 2045-2322
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Molecular Imaging and Photonics
Biochemistry, Molecular and Structural Biology Section
× corresponding author
# (joint) last author

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