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Matrix-masking to balance nonuniform illumination in microscopy

Nordenfelt, Pontus LU ; Cooper, Jonathan M. and Hochstetter, Axel (2018) In Optics Express 26(13). p.17279-17288
Abstract

With a perfectly uniform illumination, the amount and concentration of fluorophores in any (biological) sample can be read directly from fluorescence micrographs. However, non-uniform illumination in optical micrographs is a common, yet avoidable artefact, often caused by the setup of the microscope, or by inherent properties caused by the nature of the sample. In this paper, we demonstrate simple matrix-based methods using the common computing environments MATLAB and Python to correct nonuniform illumination, using either a background image or extracting illumination information directly from the sample image, together with subsequent image processing. We compare the processes, algorithms, and results obtained from both MATLAB... (More)

With a perfectly uniform illumination, the amount and concentration of fluorophores in any (biological) sample can be read directly from fluorescence micrographs. However, non-uniform illumination in optical micrographs is a common, yet avoidable artefact, often caused by the setup of the microscope, or by inherent properties caused by the nature of the sample. In this paper, we demonstrate simple matrix-based methods using the common computing environments MATLAB and Python to correct nonuniform illumination, using either a background image or extracting illumination information directly from the sample image, together with subsequent image processing. We compare the processes, algorithms, and results obtained from both MATLAB (commercially available) and Python (freeware). Additionally, we validate our method by evaluating commonly used alternative approaches, demonstrating that the best nonuniform illumination correction can be achieved when a separate background image is available.

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; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Optics Express
volume
26
issue
13
pages
10 pages
publisher
Optical Society of America
external identifiers
  • pmid:30119541
  • scopus:85049034044
ISSN
1094-4087
DOI
10.1364/OE.26.017279
language
English
LU publication?
yes
id
ad013adc-8464-42db-b18a-149e04536eb5
date added to LUP
2018-07-04 13:58:50
date last changed
2020-10-27 04:17:18
@article{ad013adc-8464-42db-b18a-149e04536eb5,
  abstract     = {<p>With a perfectly uniform illumination, the amount and concentration of fluorophores in any (biological) sample can be read directly from fluorescence micrographs. However, non-uniform illumination in optical micrographs is a common, yet avoidable artefact, often caused by the setup of the microscope, or by inherent properties caused by the nature of the sample. In this paper, we demonstrate simple matrix-based methods using the common computing environments MATLAB and Python to correct nonuniform illumination, using either a background image or extracting illumination information directly from the sample image, together with subsequent image processing. We compare the processes, algorithms, and results obtained from both MATLAB (commercially available) and Python (freeware). Additionally, we validate our method by evaluating commonly used alternative approaches, demonstrating that the best nonuniform illumination correction can be achieved when a separate background image is available.</p>},
  author       = {Nordenfelt, Pontus and Cooper, Jonathan M. and Hochstetter, Axel},
  issn         = {1094-4087},
  language     = {eng},
  month        = {06},
  number       = {13},
  pages        = {17279--17288},
  publisher    = {Optical Society of America},
  series       = {Optics Express},
  title        = {Matrix-masking to balance nonuniform illumination in microscopy},
  url          = {http://dx.doi.org/10.1364/OE.26.017279},
  doi          = {10.1364/OE.26.017279},
  volume       = {26},
  year         = {2018},
}