Literature DB >> 24974021

Assessing camera performance for quantitative microscopy.

Talley J Lambert1, Jennifer C Waters1.   

Abstract

Charge-coupled device and, increasingly, scientific complementary metal oxide semiconductor cameras are the most common digital detectors used for quantitative microscopy applications. Manufacturers provide technical specification data on the average or expected performance characteristics for each model of camera. However, the performance of individual cameras may vary, and many of the characteristics that are important for quantitation can be easily measured. Though it may seem obvious, it is important to remember that the digitized image you collect is merely a representation of the sample itself--and no camera can capture a perfect representation of an optical image. A clear understanding and characterization of the sources of noise and imprecision in your camera are important for rigorous quantitative analysis of digital images. In this chapter, we review the camera performance characteristics that are most critical for generating accurate and precise quantitative data and provide a step-by-step protocol for measuring these characteristics in your camera.
© 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  CCD; Digital cameras; Digitization; EMCCD; Noise; Photon transfer; Signal-to-noise ratio; sCMOS

Mesh:

Year:  2014        PMID: 24974021     DOI: 10.1016/B978-0-12-420138-5.00003-3

Source DB:  PubMed          Journal:  Methods Cell Biol        ISSN: 0091-679X            Impact factor:   1.441


  8 in total

1.  Semi-blind sparse affine spectral unmixing of autofluorescence-contaminated micrographs.

Authors:  Blair J Rossetti; Steven A Wilbert; Jessica L Mark Welch; Gary G Borisy; James G Nagy
Journal:  Bioinformatics       Date:  2020-02-01       Impact factor: 6.937

2.  Low Efficiency Upconversion Nanoparticles for High-Resolution Coalignment of Near-Infrared and Visible Light Paths on a Light Microscope.

Authors:  Sriramkumar Sundaramoorthy; Adrian Garcia Badaracco; Sophia M Hirsch; Jun Hong Park; Tim Davies; Julien Dumont; Mimi Shirasu-Hiza; Andrew C Kummel; Julie C Canman
Journal:  ACS Appl Mater Interfaces       Date:  2017-02-21       Impact factor: 9.229

3.  Quality assessment in light microscopy for routine use through simple tools and robust metrics.

Authors:  Orestis Faklaris; Leslie Bancel-Vallée; Aurélien Dauphin; Baptiste Monterroso; Perrine Frère; David Geny; Tudor Manoliu; Sylvain de Rossi; Fabrice P Cordelières; Damien Schapman; Roland Nitschke; Julien Cau; Thomas Guilbert
Journal:  J Cell Biol       Date:  2022-09-29       Impact factor: 8.077

4.  Towards community-driven metadata standards for light microscopy: tiered specifications extending the OME model.

Authors:  Mathias Hammer; Maximiliaan Huisman; Alessandro Rigano; Ulrike Boehm; James J Chambers; Nathalie Gaudreault; Alison J North; Jaime A Pimentel; Damir Sudar; Peter Bajcsy; Claire M Brown; Alexander D Corbett; Orestis Faklaris; Judith Lacoste; Alex Laude; Glyn Nelson; Roland Nitschke; Farzin Farzam; Carlas S Smith; David Grunwald; Caterina Strambio-De-Castillia
Journal:  Nat Methods       Date:  2021-12       Impact factor: 47.990

Review 5.  Best practices and tools for reporting reproducible fluorescence microscopy methods.

Authors:  Paula Montero Llopis; Rebecca A Senft; Tim J Ross-Elliott; Ryan Stephansky; Daniel P Keeley; Preman Koshar; Guillermo Marqués; Ya-Sheng Gao; Benjamin R Carlson; Thomas Pengo; Mark A Sanders; Lisa A Cameron; Michelle S Itano
Journal:  Nat Methods       Date:  2021-06-07       Impact factor: 28.547

Review 6.  Designing a rigorous microscopy experiment: Validating methods and avoiding bias.

Authors:  Anna Payne-Tobin Jost; Jennifer C Waters
Journal:  J Cell Biol       Date:  2019-03-20       Impact factor: 10.539

7.  Quantitative Imaging of MS2-Tagged hTR in Cajal Bodies: Photobleaching and Photoactivation.

Authors:  Michael Smith; Emmanuelle Querido; Pascal Chartrand; Agnel Sfeir
Journal:  STAR Protoc       Date:  2020-09-24

8.  Preventing Photomorbidity in Long-Term Multi-color Fluorescence Imaging of Saccharomyces cerevisiae and S. pombe.

Authors:  Gregor W Schmidt; Andreas P Cuny; Fabian Rudolf
Journal:  G3 (Bethesda)       Date:  2020-12-03       Impact factor: 3.154

  8 in total

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