Data analysis for single-molecule localization microscopy

Steve Wolter, Thorge Holm, Sebastian van de Linde, Markus Sauer

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

We review single-molecule localization microscopy techniques with a focus on computational techniques and algorithms necessary for their use. The most common approach to single-molecule localization, Gaussian fitting at positions pre-estimated from local maxima, is illustrated in depth and techniques for two- and three-dimensional data analysis are highlighted. After an introduction explaining the principle requirements of single-molecule localization microscopy, we discuss and contrast novel approaches such as maximum likelihood estimation and model-less fitting. Finally, we give an overview over the existing, scientifically available software and show how these techniques can be combined to quickly and easily obtain super-resolution images.

Original languageEnglish
Title of host publicationSuper-Resolution Microscopy Techniques in the Neurosciences
EditorsEugenio Fornasiero, Silvio Rizzoli
Place of PublicationTotowa, NJ
PublisherHumana Press
Pages113-132
Number of pages20
ISBN (Electronic)9781627039833
ISBN (Print)9781627039826
DOIs
Publication statusPublished - 21 Jan 2014

Publication series

NameNeuromethods
Volume86
ISSN (Print)0893-2336
ISSN (Electronic)1940-6045

Keywords

  • data analysis
  • dSTORM
  • localization microscopy
  • PALM
  • rapidSTORM
  • super-resolution imaging

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