Photophysical image analysis for sCMOS cameras: Noise modelling and estimation of background parameters in fluorescence-microscopy images
Mohanta, Dibyajyoti LU ; Kunnath, Radhika ; Clarkson, Erik LU
; Dvirnas, Albertas
LU
; Westerlund, Fredrik
and Ambjörnsson, Tobias
LU
(2025)
In PLOS ONE
20(11).
- 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... (More)
- 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 directly from a general sCMOS image, with camera parameters determined through calibration experiments. We validate our method by comparing 𝜆bg estimates in images captured by sCMOS and EMCCD cameras for the same field of view. Our analysis shows strong agreement for low to moderate exposure images, where estimated values for 𝜆bg align well between the sCMOS and EMCCD images. Based on our estimated 𝜆bg, we perform image thresholding and segmentation using our previously introduced procedure. Our publicly available software provides a platform for photophysical image analysis for sCMOS camera systems. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/858a9764-d502-4fb7-9be6-5423df47f9ab
- author
- Mohanta, Dibyajyoti
LU
; Kunnath, Radhika
; Clarkson, Erik
LU
; Dvirnas, Albertas
LU
; Westerlund, Fredrik
and Ambjörnsson, Tobias
LU
- organization
- publishing date
- 2025-11-04
- type
- Contribution to journal
- publication status
- published
- subject
- in
- PLOS ONE
- volume
- 20
- issue
- 11
- article number
- e0335310
- pages
- 20 pages
- publisher
- Public Library of Science (PLoS)
- external identifiers
-
- pmid:41187169
- scopus:105020733640
- ISSN
- 1932-6203
- DOI
- 10.1371/journal.pone.0335310
- language
- English
- LU publication?
- yes
- id
- 858a9764-d502-4fb7-9be6-5423df47f9ab
- date added to LUP
- 2025-11-06 15:56:29
- date last changed
- 2025-11-21 04:01:06
@article{858a9764-d502-4fb7-9be6-5423df47f9ab,
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, 𝜆<sub>bg</sub>, 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 𝜆<sub>bg</sub>, 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 𝜆<sub>bg</sub> directly from a general sCMOS image, with camera parameters determined through calibration experiments. We validate our method by comparing 𝜆<sub>bg</sub> estimates in images captured by sCMOS and EMCCD cameras for the same field of view. Our analysis shows strong agreement for low to moderate exposure images, where estimated values for 𝜆<sub>bg</sub> align well between the sCMOS and EMCCD images. Based on our estimated 𝜆<sub>bg</sub>, we perform image thresholding and segmentation using our previously introduced procedure. Our publicly available software provides a platform for photophysical image analysis for sCMOS camera systems.}},
author = {{Mohanta, Dibyajyoti and Kunnath, Radhika and Clarkson, Erik and Dvirnas, Albertas and Westerlund, Fredrik and Ambjörnsson, Tobias}},
issn = {{1932-6203}},
language = {{eng}},
month = {{11}},
number = {{11}},
publisher = {{Public Library of Science (PLoS)}},
series = {{PLOS ONE}},
title = {{Photophysical image analysis for sCMOS cameras: Noise modelling and estimation of background parameters in fluorescence-microscopy images}},
url = {{http://dx.doi.org/10.1371/journal.pone.0335310}},
doi = {{10.1371/journal.pone.0335310}},
volume = {{20}},
year = {{2025}},
}