title: Three-dimensional super-resolution structured illumination microscopy with maximum a posteriori probability image estimation.
abstract: We introduce and demonstrate a new high performance image reconstruction method for super-resolution structured illumination microscopy based on maximum a posteriori probability estimation (MAP-SIM). Imaging performance is demonstrated on a variety of fluorescent samples of different thickness, labeling density and noise levels. The method provides good suppression of out of focus light, improves spatial resolution, and allows reconstruction of both 2D and 3D images of cells even in the case of weak signals. The method can be used to process both optical sectioning and super-resolution structured illumination microscopy data to create high quality super-resolution images.
authors.forename: Tomáš
authors.initials: T
authors.lastname: Lukeš
authors.forename: Pavel
authors.initials: P
authors.lastname: Křížek
authors.forename: Zdeněk
authors.initials: Z
authors.lastname: Švindrych
authors.forename: Jakub
authors.initials: J
authors.lastname: Benda
authors.forename: Martin
authors.initials: M
authors.lastname: Ovesný
authors.forename: Karel
authors.initials: K
authors.lastname: Fliegel
authors.forename: Miloš
authors.initials: M
authors.lastname: Klíma
authors.forename: Guy M
authors.initials: GM
authors.lastname: Hagen
mesh_terms: D000465:Algorithms; D000818:Animals; D002417:Cattle; D004331:Drosophila melanogaster / Q000166:cytology; D005453:Fluorescence; D056945:Hep G2 Cells; D006801:Humans; D021621:Imaging, Three-Dimensional; D008029:Lighting; D008853:Microscopy / Q000379:methods*; D011058:Pollen / Q000166:cytology; D011336:Probability; D059629:Signal-To-Noise Ratio