Statistical molecule counting in super-resolution fluorescence microscopy: towards quantitative nanoscopy

DOI10.1214/19-STS753OpenAlexW3009767981MaRDI QIDQ2218026

Thomas Staudt, Alexander Egner, Claudia Geisler, Oskar Laitenberger, Timo Aspelmeier, Axel Munk

Publication date: 12 January 2021

Published in: Statistical Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1903.11577

zbMATH Keywords

super-resolution microscopybiophysics and computational biologyinhomogeneous hidden Markov modelsmolecule countingquantitative nanoscopystatistical thinning

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (3)

Semiparametric point process modeling of blinking artifacts in PALM ⋮ What is resolution? A statistical minimax testing perspective on superresolution microscopy ⋮ Posterior analysis of \(n\) in the binomial \((n,p)\) problem with both parameters unknown -- with applications to quantitative nanoscopy

Cites Work

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• A hidden Markov model approach to characterizing the photo-switching behavior of fluorophores
• Principles of Optics
• Thinning, Entropy, and the Law of Thin Numbers
• Drift Estimation in Sparse Sequential Dynamic Imaging, With Application to Nanoscale Fluorescence Microscopy
• A Simplex Method for Function Minimization

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