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Julia A, Iguernaissi R, Michel FJ, Matarazzo V, Merad D. Distortion Correction and Denoising of Light Sheet Fluorescence Images. SENSORS (BASEL, SWITZERLAND) 2024; 24:2053. [PMID: 38610265 PMCID: PMC11014158 DOI: 10.3390/s24072053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 03/14/2024] [Accepted: 03/20/2024] [Indexed: 04/14/2024]
Abstract
Light Sheet Fluorescence Microscopy (LSFM) has emerged as a valuable tool for neurobiologists, enabling the rapid and high-quality volumetric imaging of mice brains. However, inherent artifacts and distortions introduced during the imaging process necessitate careful enhancement of LSFM images for optimal 3D reconstructions. This work aims to correct images slice by slice before reconstructing 3D volumes. Our approach involves a three-step process: firstly, the implementation of a deblurring algorithm using the work of K. Becker; secondly, an automatic contrast enhancement; and thirdly, the development of a convolutional denoising auto-encoder featuring skip connections to effectively address noise introduced by contrast enhancement, particularly excelling in handling mixed Poisson-Gaussian noise. Additionally, we tackle the challenge of axial distortion in LSFM by introducing an approach based on an auto-encoder trained on bead calibration images. The proposed pipeline demonstrates a complete solution, presenting promising results that surpass existing methods in denoising LSFM images. These advancements hold potential to significantly improve the interpretation of biological data.
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Affiliation(s)
- Adrien Julia
- LIS, CNRS, Laboratoire d’Informatique et des Systèmes, Centre National de la Recherche Scientifique, Aix Marseille University, 13284 Marseille, France
- INMED, INSERM, Institut de Neurobiologie de la Méditerranée, Institut National de la Santé et de la Recherche Médicale, Aix Marseille University, 13284 Marseille, France; (F.J.M.)
| | - Rabah Iguernaissi
- LIS, CNRS, Laboratoire d’Informatique et des Systèmes, Centre National de la Recherche Scientifique, Aix Marseille University, 13284 Marseille, France
| | - François J. Michel
- INMED, INSERM, Institut de Neurobiologie de la Méditerranée, Institut National de la Santé et de la Recherche Médicale, Aix Marseille University, 13284 Marseille, France; (F.J.M.)
| | - Valéry Matarazzo
- INMED, INSERM, Institut de Neurobiologie de la Méditerranée, Institut National de la Santé et de la Recherche Médicale, Aix Marseille University, 13284 Marseille, France; (F.J.M.)
| | - Djamal Merad
- LIS, CNRS, Laboratoire d’Informatique et des Systèmes, Centre National de la Recherche Scientifique, Aix Marseille University, 13284 Marseille, France
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Gong D, Scherer NF. Tandem aberration correction optics (TACO) in wide-field structured illumination microscopy. BIOMEDICAL OPTICS EXPRESS 2023; 14:6381-6396. [PMID: 38420301 PMCID: PMC10898552 DOI: 10.1364/boe.503801] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 11/08/2023] [Accepted: 11/09/2023] [Indexed: 03/02/2024]
Abstract
Structured illumination microscopy (SIM) is a powerful super-resolution imaging technique that uses patterned illumination to down-modulate high spatial-frequency information of samples. However, the presence of spatially-dependent aberrations can severely disrupt the illumination pattern, limiting the quality of SIM imaging. Conventional adaptive optics (AO) techniques that employ wavefront correctors at the pupil plane are not capable of effectively correcting these spatially-dependent aberrations. We introduce the Tandem Aberration Correction Optics (TACO) approach that combines both pupil AO and conjugate AO for aberration correction in SIM. TACO incorporates a deformable mirror (DM) for pupil AO in the detection path to correct for global aberrations, while a spatial light modulator (SLM) is placed at the plane conjugate to the aberration source near the sample plane, termed conjugate AO, to compensate spatially-varying aberrations in the illumination path. Our numerical simulations and experimental results show that the TACO approach can recover the illumination pattern close to an ideal condition, even when severely misshaped by aberrations, resulting in high-quality super-resolution SIM reconstruction. The TACO approach resolves a critical traditional shortcoming of aberration correction for structured illumination. This advance significantly expands the application of SIM imaging in the study of complex, particularly biological, samples and should be effective in other wide-field microscopies.
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Affiliation(s)
- Daozheng Gong
- Graduate Program in Biophysical Sciences, University of Chicago, Chicago, IL 60637, USA
- Institute for Biophysical Dynamics, University of Chicago, Chicago, IL 60637, USA
| | - Norbert F. Scherer
- Institute for Biophysical Dynamics, University of Chicago, Chicago, IL 60637, USA
- Department of Chemistry, University of Chicago, Chicago, IL 60637, USA
- James Franck Institute, University of Chicago, Chicago, IL 60637, USA
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Furieri T, Bassi A, Bonora S. Large field of view aberrations correction with deformable lenses and multi conjugate adaptive optics. JOURNAL OF BIOPHOTONICS 2023; 16:e202300104. [PMID: 37556187 DOI: 10.1002/jbio.202300104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 07/10/2023] [Accepted: 08/07/2023] [Indexed: 08/10/2023]
Abstract
Optical microscopes can have limited resolution due to aberrations caused by samples and sample holders. Using deformable mirrors and wavefront sensorless optimization algorithms can correct these aberrations, but the correction is limited to a small area of the field of view. This study presents an adaptive optics method that uses a series of plug-and-play deformable lenses for large field of view wavefront correction. A direct wavefront measurement method using the spinning sub-pupil aberration measurement technique is combined with correction based on the deformable lenses. Experimental results using fluorescence microscopy with a wide field and a light sheet fluorescence microscope show that the proposed method can achieve detection and correction over an extended field of view with a compact transmissive module placed in the detection path of the microscope. This method could improve the resolution and accuracy of imaging in a variety of fields, including biology and materials science.
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Affiliation(s)
- T Furieri
- Institute of Photonics and Nanotechnology, National Council of Research of Italy, Padova, Italy
- Department of Information Engineering, University of Padova, Padova, Italy
| | - A Bassi
- Department of Physics, Politecnico di Milano, Milan, Italy
| | - S Bonora
- Institute of Photonics and Nanotechnology, National Council of Research of Italy, Padova, Italy
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Abstract
Multiplex imaging has emerged as an invaluable tool for immune-oncologists and translational researchers, enabling them to examine intricate interactions among immune cells, stroma, matrix, and malignant cells within the tumor microenvironment (TME). It holds significant promise in the quest to discover improved biomarkers for treatment stratification and identify novel therapeutic targets. Nonetheless, several challenges exist in the realms of study design, experiment optimization, and data analysis. In this review, our aim is to present an overview of the utilization of multiplex imaging in immuno-oncology studies and inform novice researchers about the fundamental principles at each stage of the imaging and analysis process.
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Affiliation(s)
- Chen Zhao
- Thoracic and GI Malignancies Branch, CCR, NCI, Bethesda, Maryland, USA
- Lymphocyte Biology Section, Laboratory of Immune System Biology, NIAID, Bethesda, Maryland, USA
| | - Ronald N Germain
- Lymphocyte Biology Section, Laboratory of Immune System Biology, NIAID, Bethesda, Maryland, USA
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Maddalena L, Keizers H, Pozzi P, Carroll E. Local aberration control to improve efficiency in multiphoton holographic projections. OPTICS EXPRESS 2022; 30:29128-29147. [PMID: 36299095 DOI: 10.1364/oe.463553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 06/29/2022] [Indexed: 06/16/2023]
Abstract
Optical aberrations affect the quality of light propagating through a turbid medium, where refractive index is spatially inhomogeneous. In multiphoton optical applications, such as two-photon excitation fluorescence imaging and optogenetics, aberrations non-linearly impair the efficiency of excitation. We demonstrate a sensorless adaptive optics technique to compensate aberrations in holograms projected into turbid media. We use a spatial light modulator to project custom three dimensional holographic patterns and to correct for local (anisoplanatic) distortions. The method is tested on both synthetic and biological samples to counteract aberrations arising respectively from misalignment of the optical system and from samples inhomogeneities. In both cases the anisoplanatic correction improves the intensity of the stimulation pattern at least two-fold.
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Toader B, Boulanger J, Korolev Y, Lenz MO, Manton J, Schönlieb CB, Mureşan L. Image Reconstruction in Light-Sheet Microscopy: Spatially Varying Deconvolution and Mixed Noise. JOURNAL OF MATHEMATICAL IMAGING AND VISION 2022; 64:968-992. [PMID: 36329880 PMCID: PMC7613773 DOI: 10.1007/s10851-022-01100-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Accepted: 04/23/2022] [Indexed: 06/16/2023]
Abstract
We study the problem of deconvolution for light-sheet microscopy, where the data is corrupted by spatially varying blur and a combination of Poisson and Gaussian noise. The spatial variation of the point spread function of a light-sheet microscope is determined by the interaction between the excitation sheet and the detection objective PSF. We introduce a model of the image formation process that incorporates this interaction and we formulate a variational model that accounts for the combination of Poisson and Gaussian noise through a data fidelity term consisting of the infimal convolution of the single noise fidelities, first introduced in L. Calatroni et al. (SIAM J Imaging Sci 10(3):1196-1233, 2017). We establish convergence rates and a discrepancy principle for the infimal convolution fidelity and the inverse problem is solved by applying the primal-dual hybrid gradient (PDHG) algorithm in a novel way. Numerical experiments performed on simulated and real data show superior reconstruction results in comparison with other methods.
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Affiliation(s)
- Bogdan Toader
- Cambridge Advanced Imaging Centre, University of Cambridge, Anatomy School, Downing Street, Cambridge, CB2 3DY UK
- Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Wilberforce Road, Cambridge, CB3 0WA UK
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge, CB2 3DY UK
| | - Jérôme Boulanger
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, CB2 0QH UK
| | - Yury Korolev
- Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Wilberforce Road, Cambridge, CB3 0WA UK
| | - Martin O. Lenz
- Cambridge Advanced Imaging Centre, University of Cambridge, Anatomy School, Downing Street, Cambridge, CB2 3DY UK
- Sainsbury Laboratory, University of Cambridge, 47 Bateman Street, Cambridge, CB2 1LR UK
| | - James Manton
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, CB2 0QH UK
| | - Carola-Bibiane Schönlieb
- Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Wilberforce Road, Cambridge, CB3 0WA UK
| | - Leila Mureşan
- Cambridge Advanced Imaging Centre, University of Cambridge, Anatomy School, Downing Street, Cambridge, CB2 3DY UK
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge, CB2 3DY UK
- Sainsbury Laboratory, University of Cambridge, 47 Bateman Street, Cambridge, CB2 1LR UK
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Corbetta E, Candeo A, Bassi A, Ancora D. Blind deconvolution in autocorrelation inversion for multiview light-sheet microscopy. Microsc Res Tech 2022; 85:2282-2291. [PMID: 35199902 PMCID: PMC9306839 DOI: 10.1002/jemt.24085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 12/17/2021] [Accepted: 02/09/2022] [Indexed: 11/10/2022]
Abstract
Combining the information coming from multiview acquisitions is a problem of great interest in light-sheet microscopy. Aligning the views and increasing the resolution of their fusion can be challenging, especially if the setup is not fully calibrated. Here, we tackle these issues by proposing a new reconstruction method based on autocorrelation inversion that avoids alignment procedures. On top of this, we add a blind deconvolution step to improve the resolution of the final reconstruction. Our method permits us to achieve inherently aligned, highly resolved reconstructions while, at the same time, estimating the unknown point-spread function of the system.
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Affiliation(s)
- Elena Corbetta
- Politecnico di Milano, Department of Physics, piazza Leonardo da Vinci 32, Milan, Italy
| | - Alessia Candeo
- Politecnico di Milano, Department of Physics, piazza Leonardo da Vinci 32, Milan, Italy
| | - Andrea Bassi
- Politecnico di Milano, Department of Physics, piazza Leonardo da Vinci 32, Milan, Italy.,National Council of Research of Italy, Institute of Photonics and Nanotechnology, Milan, Italy
| | - Daniele Ancora
- Politecnico di Milano, Department of Physics, piazza Leonardo da Vinci 32, Milan, Italy
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