Single-Molecule Localization Microscopy  •  Software Benchmarking

Second edition of the challenge focussed on 3D

The challenge has been presented at Single Molecule Localization Microscopy Symposium (SMLMS) at Lausanne, Switzerland, August 28-30, 2016. This edition will be focussed on 3D localization techniques, astigmatism, biplane, or double-helix.

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Super-resolution Fight Club

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S. Holden and D. Sage, News and views, Nature Photonics 10, 2016.

For the popular super-resolution imaging technique of single-molecule localization microscopy , accurately localizing the position of single fluorescent molecules is critical for success. Since localization is so central to the success of the technique, it is unsurprising that developments in localization algorithms have played a key role in improving its performance, especially in speeding up the technique. By reducing the separation required between bright molecules to accurately find their centres, so-called high-density localization algorithms have recently led to video-rate localization microscopy. The speed of localization algorithms has also increased dramatically, with run times per image having dropped from hours to seconds.

The Single Molecule Localization Microscopy Challenge was first run in 2013 and was deliberately limited to 2D datasets. We are currently organizing the second edition of the challenge and the 2016 version will focus on 3D localization microscopy. While nanoscale-resolution 3D imaging is a powerful tool for studying protein ultrastructure in vivo, it also places significant extra demands on the image analysis. 3D localization microscopy works in a similar way to its 2D counterpart, but with the additional demand of encoding the axial position of a molecule in the shape of the point spread function. This extra requirement to estimate point spread function shape makes designing effective 3D algorithms much more challenging, particularly for low signal-to-noise data. Because of this, and probably because commercial 3D localization microscopy systems were less common until recently, 3D software has seen less development and characterization than its 2D cousin. We hope to remedy this by robust testing of existing algorithms, and by creating a series of openly available simulated datasets to support future development. We are particularly keen to see how different 3D software performs away from optimal focus, since this is crucial to the effective depth of field of the technique.

Special Session at SMLMS 2017

SMLMS 2016, EPFL Lausanne

Single Molecule Localization Microscopy Symposium (SMLMS) has taken place at the Ecole Polytechnique Fédérale de Lausanne 28-30 August 2016 in Rolex Learning Center.

Webcast of the Special Session YouTube Channel, Sunday 28 August 2016, 15:00 CEST

Challenge Presentation

Instructions for reviewing manuscript NBT-RA42594

Committee • Challenge 2016

Daniel Sage

daniel.sage@epfl.ch

Biomedical Imaging Group (BIG)
Ecole Polytechnique Fédérale de Lausanne (EPFL)

Seamus Holden

seamus.holden@newcastle.ac.uk

Centre for Bacterial Cell Biology
Newcastle University, UK

Hagai Kirshner

Biomedical Imaging Group (BIG)
Ecole Polytechnique Fédérale de Lausanne (EPFL)

Thomas Pengo

Informatics Institute
University of Minnesota, USA

Ricardo Henriques

MRC-Laboratory for Molecular Cell Biology
University College London, UK

Guy Hagen

Center of the University of Colorado BioFrontiers Institute
University of Colorado at Colorado Spring (UCCS), USA

Nils Gustafsson

MRC-Laboratory for Molecular Cell Biology
University College London, UK

Hazen Babcock

Harvard Advanced Imaging Center
Harvard University, USA

Junhong Min

BIo Imaging & Signal Processing, KAIST, Korea

Bernd Rieger

Quantitative Imaging Group
Delft University of Technology, The Netherlands

Tomas Lukes

Laboratoire d'Optique Bioédciale (LOB)
Ecole Polytechnique Fédérale de Lausanne (EPFL)

Martin Ovesný

Charles University, Prague, Czech Republic

Jean-Baptiste Sibarita

Imagerie Cellulaire Quantitative
Université de Bordeaux, France

Silvia Colabrese

Pattern Analysis and Computer Vision
Italian Institute of Technology, Italy

Anna Archetti

Laboratory of Experimental Biophysics (LEB)
Ecole Polytechnique Fédérale de Lausanne (EPFL)

Thanh-An Pham

Biomedical Imaging Group (BIG)
Ecole Polytechnique Fédérale de Lausanne (EPFL)

Sponsors • Challenge 2016

SMLMS 2016

The challenge was sponsored by the sponsors of the symposium SMLMS 2016 organized by Aleksandra Radenovic and Suliana Manley, EPFL.

smlms.epfl.ch

Nikon

https://www.nikoninstruments.com/

© 2017 Biomedical Imaging Group, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Last update: 31 Mar 2017