Literature DB >> 33501207

Detecting Differences of Fluorescent Markers Distribution in Single Cell Microscopy: Textural or Pointillist Feature Space?

Ali Ahmad1,2, Carole Frindel2, David Rousseau1.   

Abstract

We consider the detection of change in spatial distribution of fluorescent markers inside cells imaged by single cell microscopy. Such problems are important in bioimaging since the density of these markers can reflect the healthy or pathological state of cells, the spatial organization of DNA, or cell cycle stage. With the new super-resolved microscopes and associated microfluidic devices, bio-markers can be detected in single cells individually or collectively as a texture depending on the quality of the microscope impulse response. In this work, we propose, via numerical simulations, to address detection of changes in spatial density or in spatial clustering with an individual (pointillist) or collective (textural) approach by comparing their performances according to the size of the impulse response of the microscope. Pointillist approaches show good performances for small impulse response sizes only, while all textural approaches are found to overcome pointillist approaches with small as well as with large impulse response sizes. These results are validated with real fluorescence microscopy images with conventional resolution. This, a priori non-intuitive result in the perspective of the quest of super-resolution, demonstrates that, for difference detection tasks in single cell microscopy, super-resolved microscopes may not be mandatory and that lower cost, sub-resolved, microscopes can be sufficient.
Copyright © 2020 Ahmad, Frindel and Rousseau.

Entities:  

Keywords:  classification; fluorescence; microscopy; point spread function; spot detection; texture

Year:  2020        PMID: 33501207      PMCID: PMC7805927          DOI: 10.3389/frobt.2020.00039

Source DB:  PubMed          Journal:  Front Robot AI        ISSN: 2296-9144


  30 in total

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