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Deconvolution 3D

F. Soulez, D. Sage

Proceedings of the Ninth Edition of the CNRS Thematic School, Functional Microscopy for Biology (MiFoBio'21), Presqu'île de Giens, French Republic, November 5-12, 2021, pp. 108-109


Le but de la déconvolution est de compenser numériquement le flou introduit par le microscope. En microscopie 3D, la déconvolution permet d'améliorer les images sur plusieurs points:

  • en améliorant la résolution (axiale en particulier),
  • en diminuant le bruit (en particulier à faible flux),
  • en améliorant le contraste.

Cela fait de la déconvolution un outil précieux pour améliorer les post traitements comme la segmentation.

Cet atelier propose de démystifier les méthodes de déconvolution et propose une prise en main des logiciels libres de deconvolution.

Il sera en 4 parties:

  • une brève description théorique,
  • les points importants pour une déconvolution réussie: conditions d'acquisition
  • comment avoir une bonne PSF
  • illustration des méthodes classiques avec le plugin DeconvolutionLab2 sur des données simulées et réelles
  • dans le cas où la PSF n'est pas connue nous guiderons les utilisateurs dans l'utilisation de plugins de déconvolution aveugle ou myope

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AUTHOR="Soulez, F. and Sage, D.",
TITLE="Deconvolution 3D",
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	School, Functional Microscopy for Biology ({MiFoBio'21})",
YEAR="2021",
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pages="108--109",
address="Presqu'{\^{i}}le de Giens, French Republic",
month="November 7-12,",
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