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Journal Articles Journal of Mathematical Imaging and Vision Year : 2021

Efficient segmentation and positioning of 3D fluorescent spherical beads in confocal microscopy

Abstract

Particle estimation is a classical problem arising in many science fields, such as biophysics, fluid mechanics, bio-medical imaging. Many interesting applications in these areas involve 3D data: this work presents a technique to estimate the 3D coordinates of the center of spherical particles. This procedure provides an estimation of both the center and the profile of the 2D intersections of the particles with the frames, by coupling the usage of Total Variation functional and of a regularized weighted Least Square fit. The 2D information is used to retrieve the 3D coordinates using geometrical properties. The performance of this procedure strongly depends on the quality of the acquisition, hence a particularly tailored denoising technique is applied for Poisson noise: this leads to a better estimation of the particle positions.
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Dates and versions

hal-02150316 , version 1 (07-06-2019)
hal-02150316 , version 2 (05-09-2019)
hal-02150316 , version 3 (02-10-2019)
hal-02150316 , version 4 (28-07-2020)
hal-02150316 , version 5 (19-02-2021)

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Cite

Alessandro Benfenati, Francesco Bonacci, Tarik Bourouina, Hugues Talbot. Efficient segmentation and positioning of 3D fluorescent spherical beads in confocal microscopy. Journal of Mathematical Imaging and Vision, 2021, 63 (1), pp.56-72. ⟨10.1007/s10851-020-00994-1⟩. ⟨hal-02150316v1⟩
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