title: Sparse deconvolution of high-density super-resolution images.
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.
authors.affiliation: Université de Lille, LASIR CNRS UMR 8516, F-59000 Lille, France.
authors.forename: Siewert
authors.initials: S
authors.lastname: Hugelier
authors.affiliation: Erasmus MC, Department of Biostatistics, Rotterdam, the Netherlands.|Swammerdam Institute for Life Sciences (Universiteit van Amsterdam), 1098 XH Amsterdam, The Netherlands.
authors.forename: Johan J
authors.initials: JJ
authors.lastname: de Rooi
authors.affiliation: Université de Lille, LASIR CNRS UMR 8516, F-59000 Lille, France.
authors.forename: Romain
authors.initials: R
authors.lastname: Bernex
authors.affiliation: Department of Chemistry, KU Leuven, Belgium.
authors.forename: Sam
authors.initials: S
authors.lastname: Duwé
authors.affiliation: Université de Lille, LASIR CNRS UMR 8516, F-59000 Lille, France.
authors.forename: Olivier
authors.initials: O
authors.lastname: Devos
authors.affiliation: Université de Lille, LASIR CNRS UMR 8516, F-59000 Lille, France.
authors.forename: Michel
authors.initials: M
authors.lastname: Sliwa
authors.affiliation: Department of Chemistry, KU Leuven, Belgium.
authors.forename: Peter
authors.initials: P
authors.lastname: Dedecker
authors.affiliation: Erasmus MC, Department of Biostatistics, Rotterdam, the Netherlands.
authors.forename: Paul H C
authors.initials: PH
authors.lastname: Eilers
authors.affiliation: Université de Lille, LASIR CNRS UMR 8516, F-59000 Lille, France.
authors.forename: Cyril
authors.initials: C
authors.lastname: Ruckebusch
mesh_terms: D000465:Algorithms; D005456:Fluorescent Dyes / Q000737:chemistry / Q000378:metabolism; D057809:HEK293 Cells; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008856:Microscopy, Fluorescence; D008928:Mitochondria / Q000473:pathology
chemical_list: D005456:Fluorescent Dyes