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Communication Dans Un Congrès Année : 2016

Denoising 3D microscopy images of cell nuclei using shape priors on an anisotropic grid

Résumé

This paper presents a new multiscale method to denoise three-dimensional images of cell nuclei. The speci- ficity of this method is its awareness of the noise distribution and object shapes. It combines a multiscale representation called Isotropic Undecimated Wavelet Transform (IUWT) with a nonlinear transform, a statistical test and a variational method, to retrieve spherical shapes in the image. Beyond extending an existing 2D approach to a 3D problem, our algorithm takes the sampling grid dimensions into account. We compare our method to the two algorithms from which it is derived on a representative image analysis task, and show that it is superior to both of them. It brings a slight improvement in the signal-to-noise ratio and a significant improvement in cell detection.
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Dates et versions

hal-01558022 , version 1 (03-06-2020)

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Paternité - Partage selon les Conditions Initiales

Identifiants

  • HAL Id : hal-01558022 , version 1
  • PRODINRA : 396728

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Mathieu Bouyrie, Cristina Manfredotti, Nadine Peyriéras, Antoine Cornuéjols. Denoising 3D microscopy images of cell nuclei using shape priors on an anisotropic grid. ICPRAM 2016 International Conference on Pattern Recognition Applications and Method, Feb 2016, Rome, Italy. ⟨hal-01558022⟩
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