Photophysical image analysis for sCMOS cameras: Noise modelling and estimation of background parameters in fluorescence-microscopy images
Dibyajyoti Mohanta, Radhika Nambannor Kunnath, Erik Clarkson, Albertas Dvirnas, Fredrik Westerlund, Tobias Ambjörnsson, Hafiz Muhammad Umer Farooqi, Hafiz Muhammad Umer Farooqi, Hafiz Muhammad Umer Farooqi
TL;DR
This paper introduces a new method to estimate background photon levels in fluorescence microscopy images using sCMOS cameras, improving image analysis accuracy.
Contribution
A novel probabilistic noise modeling approach for sCMOS cameras to estimate the Poisson parameter λbg directly from images.
Findings
The method estimates λbg using a chi-square test and truncated fit technique with strong agreement between sCMOS and EMCCD cameras for low to moderate exposure images.
The approach incorporates Poisson-distributed photon shot noise and Tukey-Lambda read noise modeling for accurate background estimation.
Publicly available software enables photophysical image analysis for sCMOS systems.
Abstract
Fluorescence microscopy is an effective tool for imaging biological samples, yet captured images often contain noises, including photon shot noise and camera read noise. To analyze biological samples accurately, separating background pixels from signal pixels is crucial. This would ideally be guided by the knowledge of a parameter called the Poisson parameter, λbg, representing the mean number of photons collected in a background pixel (for the case when quantum efficiency = 1 and the dark current is negligible). This study introduces a method for estimating λbg, from an image which contains both background and signal pixels, using probabilistic noise modeling for an sCMOS camera. The approach incorporates Poisson-distributed photon shot noise and sCMOS camera read noise modelled with a Tukey-Lambda distribution. We apply a chi-square test and a truncated fit technique to estimate λbg…
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Taxonomy
TopicsAdvanced Fluorescence Microscopy Techniques · CCD and CMOS Imaging Sensors · Cell Image Analysis Techniques