Abstract

In order to count photons with a camera, the camera must be calibrated. Photon counting is necessary, e.g., to determine the precision of localization-based super-resolution microscopy. Here we present a protocol that calibrates an EMCCD camera from information contained in isolated, diffraction-limited spots in any image taken by the camera, thus making dedicated calibration procedures redundant by enabling calibration post festum, from images filed without calibration information.

Highlights

  • In bio-science and -technology, the nanoscale is investigated with optical microscopy by observing fluorescent probes attached to biological structures of interest

  • What matters is that isolated point-sources image as isolated diffraction limited spots, and that one knows the point spread function (PSF) for such sources

  • For better statistics, one fits PSFs to several different isolated point sources in an image and/or to different images of the same spot imaged as a time-lapse movie

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Summary

Introduction

In bio-science and -technology, the nanoscale is investigated with optical microscopy by observing fluorescent probes attached to biological structures of interest. Are distributions of fluorophores, e.g. to track moving biological filaments[7] or DNA in nanochannels[8] All these methods overcome the diffraction limit of conventional fluorescence microscopy by fitting theoretical intensity profiles to experimental diffraction-limited intensity distributions that typically are recorded with an electron-multiplying CCD (EMCCD) camera. One can calibrate from any image if one knows which pixels record identical intensities of light Any set of such pixels have the same expected value, v, for the number of photons they register, and have the same expected value for their output signals, S = Gv. The actual number of photons that falls on any of these pixels is a random integer, Poisson distributed with expected value v. Given such data for a range of light intensities, the parameters G and Soffset in equation 2 are determined by fitting a straight line to these data[12,13]

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