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Article Dans Une Revue Bioinformatics Année : 2020

3D Flow Field Estimation and Assessment for Live Cell Fluorescence Microscopy

Résumé

Motivation: The revolution in light sheet microscopy enables the concurrent observation of thousands of dynamic processes, from single molecules to cellular organelles, with high spatiotemporal resolution. However, challenges in the interpretation of multidimensional data requires the fully automatic measurement of those motions to link local processes to cellular functions. This includes the design and the implementation of image processing pipelines able to deal with diverse motion types, and 3D visualization tools adapted to the human visual system. Results: Here, we describe a new method for 3D motion estimation that addresses the aforementioned issues. We integrate 3D matching and variational approach to handle a diverse range of motion without any prior on the shape of moving objects. We compare di erent similarity measures to cope with intensity ambiguities and demonstrate the e ectiveness of the Census signature for both stages. Additionally, we present two intuitive visualization approaches to adapt complex 3D measures into an interpretable 2D view, and a novel way to assess the quality of flow estimates in absence of ground truth.
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Dates et versions

hal-02308001 , version 1 (08-10-2019)

Identifiants

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Sandeep Manandhar, Patrick Bouthemy, Erik Welf, Gaudenz Danuser, Philippe Roudot, et al.. 3D Flow Field Estimation and Assessment for Live Cell Fluorescence Microscopy. Bioinformatics, 2020, 36 (5), pp.1317-1325. ⟨10.1093/bioinformatics/btz780⟩. ⟨hal-02308001⟩
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