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Wang S, Bai C, Li X, Qian J, Li R, Peng T, Tian X, Ma W, Ma R, An S, Gao P, Dan D, Yao B. Parameter-free super-resolution structured illumination microscopy via a physics-enhanced neural network. OPTICS LETTERS 2024; 49:4855-4858. [PMID: 39207981 DOI: 10.1364/ol.533164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2024] [Accepted: 08/06/2024] [Indexed: 09/04/2024]
Abstract
With full-field imaging and high photon efficiency advantages, structured illumination microscopy (SIM) is one of the most potent super-resolution (SR) modalities in bioscience. Regarding SR reconstruction for SIM, spatial domain reconstruction (SDR) has been proven to be faster than traditional frequency domain reconstruction (FDR), facilitating real-time imaging of live cells. Nevertheless, SDR relies on high-precision parameter estimation for reconstruction, which tends to suffer from low signal-to-noise ratio (SNR) conditions and inevitably leads to artifacts that seriously affect the accuracy of SR reconstruction. In this Letter, a physics-enhanced neural network-based parameter-free SDR (PNNP-SDR) is proposed, which can achieve SR reconstruction directly in the spatial domain. As a result, the peak-SNR (PSNR) of PNNP-SDR is improved by about 4 dB compared to the cross-correlation (COR) SR reconstruction; meanwhile, the reconstruction speed of PNNP-SDR is even about five times faster than the fast approach based on principal component analysis (PCA). Given its capability of achieving parameter-free imaging, noise robustness, and high-fidelity and high-speed SR reconstruction over conventional SIM microscope hardware, the proposed PNNP-SDR is expected to be widely adopted in biomedical SR imaging scenarios.
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2
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Ward EN, McClelland RM, Lamb JR, Rubio-Sánchez R, Christensen CN, Mazumder B, Kapsiani S, Mascheroni L, Di Michele L, Kaminski Schierle GS, Kaminski CF. Fast, multicolour optical sectioning over extended fields of view with patterned illumination and machine learning. BIOMEDICAL OPTICS EXPRESS 2024; 15:1074-1088. [PMID: 38404329 PMCID: PMC10890859 DOI: 10.1364/boe.510912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 12/22/2023] [Accepted: 01/09/2024] [Indexed: 02/27/2024]
Abstract
Structured illumination can reject out-of-focus signal from a sample, enabling high-speed and high-contrast imaging over large areas with widefield detection optics. However, this optical sectioning technique is currently limited by image reconstruction artefacts and poor performance at low signal-to-noise ratios. We combine multicolour interferometric pattern generation with machine learning to achieve high-contrast, real-time reconstruction of image data that is robust to background noise and sample motion. We validate the method in silico and demonstrate imaging of diverse specimens, from fixed and live biological samples to synthetic biosystems, reconstructing data live at 11 Hz across a 44 × 44μm2 field of view, and demonstrate image acquisition speeds exceeding 154 Hz.
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Affiliation(s)
- Edward N. Ward
- Department of Chemical Engineering and
Biotechnology, University of Cambridge, Cambridge, CB3 0AS, UK
| | - Rebecca M. McClelland
- Department of Chemical Engineering and
Biotechnology, University of Cambridge, Cambridge, CB3 0AS, UK
| | - Jacob R. Lamb
- Department of Chemical Engineering and
Biotechnology, University of Cambridge, Cambridge, CB3 0AS, UK
| | - Roger Rubio-Sánchez
- Department of Chemical Engineering and
Biotechnology, University of Cambridge, Cambridge, CB3 0AS, UK
- fabriCELL, Molecular Sciences Research Hub,
Imperial College London, London, W12 0BZ,
UK
| | - Charles N. Christensen
- Department of Chemical Engineering and
Biotechnology, University of Cambridge, Cambridge, CB3 0AS, UK
| | - Bismoy Mazumder
- Department of Chemical Engineering and
Biotechnology, University of Cambridge, Cambridge, CB3 0AS, UK
| | - Sofia Kapsiani
- Department of Chemical Engineering and
Biotechnology, University of Cambridge, Cambridge, CB3 0AS, UK
| | - Luca Mascheroni
- Department of Chemical Engineering and
Biotechnology, University of Cambridge, Cambridge, CB3 0AS, UK
| | - Lorenzo Di Michele
- Department of Chemical Engineering and
Biotechnology, University of Cambridge, Cambridge, CB3 0AS, UK
- fabriCELL, Molecular Sciences Research Hub,
Imperial College London, London, W12 0BZ,
UK
| | | | - Clemens F. Kaminski
- Department of Chemical Engineering and
Biotechnology, University of Cambridge, Cambridge, CB3 0AS, UK
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3
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Gong D, Cai C, Strahilevitz E, Chen J, Scherer NF. Easily scalable multi-color DMD-based structured illumination microscopy. OPTICS LETTERS 2024; 49:77-80. [PMID: 38134158 DOI: 10.1364/ol.507599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 12/04/2023] [Indexed: 12/24/2023]
Abstract
Structured illumination microscopy (SIM) achieves super-resolution imaging using a series of phase-shifted sinusoidal illumination patterns to down-modulate high spatial-frequency information of samples. Digital micromirror devices (DMDs) have been increasingly used to generate SIM illumination patterns due to their high speed and moderate cost. However, a DMD micromirror array's blazed grating structure causes strong angular dispersion for different wavelengths of light, thus severely hampering its application in multicolor imaging. We developed a multi-color DMD-SIM setup that employs a diffraction grating to compensate the DMD's dispersion and demonstrate super-resolution SIM imaging of both fluorescent beads and live cells samples with four color channels. This simple but effective approach can be readily scaled to more color channels, thereby greatly expanding the application of SIM in the study of complex multi-component structures and dynamics in soft matter systems.
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Chen X, Zhong S, Hou Y, Cao R, Wang W, Li D, Dai Q, Kim D, Xi P. Superresolution structured illumination microscopy reconstruction algorithms: a review. LIGHT, SCIENCE & APPLICATIONS 2023; 12:172. [PMID: 37433801 DOI: 10.1038/s41377-023-01204-4] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 05/24/2023] [Accepted: 06/05/2023] [Indexed: 07/13/2023]
Abstract
Structured illumination microscopy (SIM) has become the standard for next-generation wide-field microscopy, offering ultrahigh imaging speed, superresolution, a large field-of-view, and long-term imaging. Over the past decade, SIM hardware and software have flourished, leading to successful applications in various biological questions. However, unlocking the full potential of SIM system hardware requires the development of advanced reconstruction algorithms. Here, we introduce the basic theory of two SIM algorithms, namely, optical sectioning SIM (OS-SIM) and superresolution SIM (SR-SIM), and summarize their implementation modalities. We then provide a brief overview of existing OS-SIM processing algorithms and review the development of SR-SIM reconstruction algorithms, focusing primarily on 2D-SIM, 3D-SIM, and blind-SIM. To showcase the state-of-the-art development of SIM systems and assist users in selecting a commercial SIM system for a specific application, we compare the features of representative off-the-shelf SIM systems. Finally, we provide perspectives on the potential future developments of SIM.
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Affiliation(s)
- Xin Chen
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, 100871, China
- National Biomedical Imaging Center, Peking University, Beijing, 100871, China
| | - Suyi Zhong
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, 100871, China
- National Biomedical Imaging Center, Peking University, Beijing, 100871, China
| | - Yiwei Hou
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, 100871, China
- National Biomedical Imaging Center, Peking University, Beijing, 100871, China
| | - Ruijie Cao
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, 100871, China
- National Biomedical Imaging Center, Peking University, Beijing, 100871, China
| | - Wenyi Wang
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, 100871, China
- National Biomedical Imaging Center, Peking University, Beijing, 100871, China
| | - Dong Li
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Qionghai Dai
- Department of Automation, Tsinghua University, Beijing, China
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, China
- Beijing Key Laboratory of Multidimension & Multiscale Computational Photography, Tsinghua University, Beijing, China
- Beijing Laboratory of Brain and Cognitive Intelligence, Beijing Municipal Education Commission, Beijing, China
| | - Donghyun Kim
- School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-Ro, Seodaemun-Gu, Seoul, 03722, Korea
| | - Peng Xi
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, 100871, China.
- National Biomedical Imaging Center, Peking University, Beijing, 100871, China.
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Fang X, Wen K, An S, Zheng J, Li J, Zalevsky Z, Gao P. Reconstruction algorithm using 2N+1 raw images for structured illumination microscopy. JOURNAL OF THE OPTICAL SOCIETY OF AMERICA. A, OPTICS, IMAGE SCIENCE, AND VISION 2023; 40:765-773. [PMID: 37132974 DOI: 10.1364/josaa.483884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
This paper presents a structured illumination microscopy (SIM) reconstruction algorithm that allows the reconstruction of super-resolved images with 2N + 1 raw intensity images, with N being the number of structured illumination directions used. The intensity images are recorded after using a 2D grating for the projection fringe and a spatial light modulator to select two orthogonal fringe orientations and perform phase shifting. Super-resolution images can be reconstructed from the five intensity images, enhancing the imaging speed and reducing the photobleaching by 17%, compared to conventional two-direction and three-step phase-shifting SIM. We believe the proposed technique will be further developed and widely applied in many fields.
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Chen X, Hou Y, Xi P. Parameter estimation of the structured illumination pattern based on principal component analysis (PCA): PCA-SIM. LIGHT, SCIENCE & APPLICATIONS 2023; 12:41. [PMID: 36755013 PMCID: PMC9908970 DOI: 10.1038/s41377-022-01043-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Principal component analysis (PCA), a common dimensionality reduction method, is introduced into SIM to identify the frequency vectors and pattern phases of the illumination pattern with precise subpixel accuracy, fast speed, and noise-robustness, which is promising for real-time and long-term live-cell imaging.
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Affiliation(s)
- Xin Chen
- Department of Biomedical Engineering, College of Future Technology, Peking University, 100871, Beijing, China
- National Biomedical Imaging Center, Peking University, 100871, Beijing, China
| | - Yiwei Hou
- Department of Biomedical Engineering, College of Future Technology, Peking University, 100871, Beijing, China
- National Biomedical Imaging Center, Peking University, 100871, Beijing, China
| | - Peng Xi
- Department of Biomedical Engineering, College of Future Technology, Peking University, 100871, Beijing, China.
- National Biomedical Imaging Center, Peking University, 100871, Beijing, China.
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Acuña-Rodriguez JP, Mena-Vega JP, Argüello-Miranda O. Live-cell fluorescence spectral imaging as a data science challenge. Biophys Rev 2022; 14:579-597. [PMID: 35528031 PMCID: PMC9043069 DOI: 10.1007/s12551-022-00941-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 03/09/2022] [Indexed: 12/13/2022] Open
Abstract
Live-cell fluorescence spectral imaging is an evolving modality of microscopy that uses specific properties of fluorophores, such as excitation or emission spectra, to detect multiple molecules and structures in intact cells. The main challenge of analyzing live-cell fluorescence spectral imaging data is the precise quantification of fluorescent molecules despite the weak signals and high noise found when imaging living cells under non-phototoxic conditions. Beyond the optimization of fluorophores and microscopy setups, quantifying multiple fluorophores requires algorithms that separate or unmix the contributions of the numerous fluorescent signals recorded at the single pixel level. This review aims to provide both the experimental scientist and the data analyst with a straightforward description of the evolution of spectral unmixing algorithms for fluorescence live-cell imaging. We show how the initial systems of linear equations used to determine the concentration of fluorophores in a pixel progressively evolved into matrix factorization, clustering, and deep learning approaches. We outline potential future trends on combining fluorescence spectral imaging with label-free detection methods, fluorescence lifetime imaging, and deep learning image analysis.
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Affiliation(s)
- Jessy Pamela Acuña-Rodriguez
- Center for Geophysical Research (CIGEFI), University of Costa Rica, San Pedro, San José Costa Rica
- School of Physics, University of Costa Rica, 2060 San Pedro, San José Costa Rica
| | - Jean Paul Mena-Vega
- School of Physics, University of Costa Rica, 2060 San Pedro, San José Costa Rica
| | - Orlando Argüello-Miranda
- Department of Plant and Microbial Biology, North Carolina State University, 112 DERIEUX PLACE, Raleigh, NC 27695-7612 USA
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Opstad IS, Godtliebsen G, Ahluwalia BS, Myrmel T, Agarwal K, Birgisdottir ÅB. Mitochondrial dynamics and quantification of mitochondria-derived vesicles in cardiomyoblasts using structured illumination microscopy. JOURNAL OF BIOPHOTONICS 2022; 15:e202100305. [PMID: 34766731 DOI: 10.1002/jbio.202100305] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 11/09/2021] [Accepted: 11/09/2021] [Indexed: 05/20/2023]
Abstract
Mitochondria are essential energy-providing organelles of particular importance in energy-demanding tissue such as the heart. The production of mitochondria-derived vesicles (MDVs) is a cellular mechanism by which cells ensure a healthy pool of mitochondria. These vesicles are small and fast-moving objects not easily captured by imaging. In this work, we have tested the ability of the optical super-resolution technique 3DSIM to capture high-resolution images of MDVs. We optimized the imaging conditions both for high-speed video microscopy and fixed-cell imaging and analysis. From the 3DSIM videos, we observed an abundance of MDVs and many dynamic mitochondrial tubules. The density of MDVs in cells was compared for cells under normal growth conditions and cells during metabolic perturbation. Our results indicate a higher abundance of MDVs in H9c2 cells during glucose deprivation compared with cells under normal growth conditions. Furthermore, the results reveal a large untapped potential of 3DSIM in MDV research.
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Affiliation(s)
- Ida S Opstad
- Department of Physics and Technology, UiT - The Arctic University of Norway, Tromsø, Norway
| | - Gustav Godtliebsen
- Department of Clinical Medicine, UiT - The Arctic University of Norway, Tromsø, Norway
| | - Balpreet Singh Ahluwalia
- Department of Physics and Technology, UiT - The Arctic University of Norway, Tromsø, Norway
- Department of Clinical Science, Intervention and Technology, Karolinska Institute, Stockholm, Sweden
| | - Truls Myrmel
- Department of Clinical Medicine, UiT - The Arctic University of Norway, Tromsø, Norway
- Division of Cardiothoracic and Respiratory Medicine, University Hospital of North Norway, Tromsø, Norway
| | - Krishna Agarwal
- Department of Physics and Technology, UiT - The Arctic University of Norway, Tromsø, Norway
| | - Åsa Birna Birgisdottir
- Department of Clinical Medicine, UiT - The Arctic University of Norway, Tromsø, Norway
- Division of Cardiothoracic and Respiratory Medicine, University Hospital of North Norway, Tromsø, Norway
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9
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Meglinski I, Novikova T, Dholakia K. Polarization and Orbital Angular Momentum of Light in Biomedical Applications: feature issue introduction. BIOMEDICAL OPTICS EXPRESS 2021; 12:6255-6258. [PMID: 34745733 PMCID: PMC8548002 DOI: 10.1364/boe.442828] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Indexed: 05/25/2023]
Abstract
In the last decade, consistent and successful innovations have been achieved in the field of lasers and optics, collectively known as 'photonics', founding new applications in biomedicine, including clinical biopsy. Non-invasive photonics-based diagnostic modalities are rapidly expanding, and with their exponential improvement, there is a great potential to develop practical instrumentation for automatic detection and identification of different types and/or sub-types of diseases at a very early stage. While using conventional light for the studies of different properties of objects in materials science, astrophysics and biomedicine already has a long history, the interaction of polarized light and optical angular momentum with turbid tissue-like scattering media has not yet been ultimately explored. Since recently this research area became a hot topic. This feature issue is a first attempt to summarize the recognitions achieved in this emerging research field of polarized light and optical angular momentum for practical biomedical applications during the last years.
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Affiliation(s)
- Igor Meglinski
- College of Engineering and Physical Science, Aston University, Birmingham, B4 7ET, United Kingdom
- Institute of Clinical Medicine N.V. Sklifosovsky, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
- Optoelectronics and Measurement Techniques, ITEE, University of Oulu, Oulu, Finland
| | - Tatiana Novikova
- LPICM, CNRS, Ecole Polytechnique, Institut Polytechnique de Paris, Palaiseau, France
- Department of Biomedical Engineering, College of Engineering and Computing, Florida International University, Miami, FL 33174, USA
| | - Kishan Dholakia
- SUPA, School of Physics & Astronomy, University of St. Andrews, St. Andrews, KY16 9SS, United Kingdom
- Department of Physics, College of Science, Yonsei University, Seoul 03722, Republic of Korea
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