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Mazzella L, Mangeat T, Giroussens G, Rogez B, Li H, Creff J, Saadaoui M, Martins C, Bouzignac R, Labouesse S, Idier J, Galland F, Allain M, Sentenac A, LeGoff L. Extended-depth of field random illumination microscopy, EDF-RIM, provides super-resolved projective imaging. LIGHT, SCIENCE & APPLICATIONS 2024; 13:285. [PMID: 39384765 PMCID: PMC11479626 DOI: 10.1038/s41377-024-01612-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 08/15/2024] [Accepted: 08/27/2024] [Indexed: 10/11/2024]
Abstract
The ultimate aim of fluorescence microscopy is to achieve high-resolution imaging of increasingly larger biological samples. Extended depth of field presents a potential solution to accelerate imaging of large samples when compression of information along the optical axis is not detrimental to the interpretation of images. We have implemented an extended depth of field (EDF) approach in a random illumination microscope (RIM). RIM uses multiple speckled illuminations and variance data processing to double the resolution. It is particularly adapted to the imaging of thick samples as it does not require the knowledge of illumination patterns. We demonstrate highly-resolved projective images of biological tissues and cells. Compared to a sequential scan of the imaged volume with conventional 2D-RIM, EDF-RIM allows an order of magnitude improvement in speed and light dose reduction, with comparable resolution. As the axial information is lost in an EDF modality, we propose a method to retrieve the sample topography for samples that are organized in cell sheets.
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Affiliation(s)
- Lorry Mazzella
- Aix Marseille Université, CNRS, Centrale Med, Institut Fresnel UMR7249, Turing Center for Living Systems, Marseille, France
| | - Thomas Mangeat
- LITC Core Facility, Centre de Biologie Integrative (CBI), CNRS, Université de Toulouse, UT3, Toulouse, France
| | - Guillaume Giroussens
- Aix Marseille Université, CNRS, Centrale Med, Institut Fresnel UMR7249, Turing Center for Living Systems, Marseille, France
| | - Benoit Rogez
- Aix Marseille Université, CNRS, Centrale Med, Institut Fresnel UMR7249, Turing Center for Living Systems, Marseille, France
| | - Hao Li
- MCD, Centre de Biologie Intégrative (CBI), CNRS, Université de Toulouse, UT3, Toulouse, France
| | - Justine Creff
- MCD, Centre de Biologie Intégrative (CBI), CNRS, Université de Toulouse, UT3, Toulouse, France
| | - Mehdi Saadaoui
- Aix Marseille University, CNRS, IBDM UMR7288, Turing Centre for Living Systems, Marseille, France
| | - Carla Martins
- Aix Marseille Université, CNRS, Centrale Med, Institut Fresnel UMR7249, Turing Center for Living Systems, Marseille, France
| | - Ronan Bouzignac
- MCD, Centre de Biologie Intégrative (CBI), CNRS, Université de Toulouse, UT3, Toulouse, France
| | - Simon Labouesse
- LITC Core Facility, Centre de Biologie Integrative (CBI), CNRS, Université de Toulouse, UT3, Toulouse, France
| | - Jérome Idier
- LS2N, CNRS UMR 6004, F44321, Nantes Cedex 3, France
| | - Frédéric Galland
- Aix Marseille Université, CNRS, Centrale Med, Institut Fresnel UMR7249, Turing Center for Living Systems, Marseille, France
| | - Marc Allain
- Aix Marseille Université, CNRS, Centrale Med, Institut Fresnel UMR7249, Turing Center for Living Systems, Marseille, France
| | - Anne Sentenac
- Aix Marseille Université, CNRS, Centrale Med, Institut Fresnel UMR7249, Turing Center for Living Systems, Marseille, France.
| | - Loïc LeGoff
- Aix Marseille Université, CNRS, Centrale Med, Institut Fresnel UMR7249, Turing Center for Living Systems, Marseille, France.
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Gilet V, Mabilleau G, Loumaigne M, Coic L, Vitale R, Oberlin T, de Morais Goulart JH, Dobigeon N, Ruckebusch C, Rousseau D. Superpixels meet essential spectra for fast Raman hyperspectral microimaging. OPTICS EXPRESS 2024; 32:932-948. [PMID: 38175114 DOI: 10.1364/oe.509736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 12/02/2023] [Indexed: 01/05/2024]
Abstract
In the context of spectral unmixing, essential information corresponds to the most linearly dissimilar rows and/or columns of a two-way data matrix which are indispensable to reproduce the full data matrix in a convex linear way. Essential information has recently been shown accessible on-the-fly via a decomposition of the measured spectra in the Fourier domain and has opened new perspectives for fast Raman hyperspectral microimaging. In addition, when some spatial prior is available about the sample, such as the existence of homogeneous objects in the image, further acceleration for the data acquisition procedure can be achieved by using superpixels. The expected gain in acquisition time is shown to be around three order of magnitude on simulated and real data with very limited distortions of the estimated spectrum of each object composing the images.
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