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Huang Z, Cao L. Quantitative phase imaging based on holography: trends and new perspectives. LIGHT, SCIENCE & APPLICATIONS 2024; 13:145. [PMID: 38937443 PMCID: PMC11211409 DOI: 10.1038/s41377-024-01453-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Revised: 04/07/2024] [Accepted: 04/10/2024] [Indexed: 06/29/2024]
Abstract
In 1948, Dennis Gabor proposed the concept of holography, providing a pioneering solution to a quantitative description of the optical wavefront. After 75 years of development, holographic imaging has become a powerful tool for optical wavefront measurement and quantitative phase imaging. The emergence of this technology has given fresh energy to physics, biology, and materials science. Digital holography (DH) possesses the quantitative advantages of wide-field, non-contact, precise, and dynamic measurement capability for complex-waves. DH has unique capabilities for the propagation of optical fields by measuring light scattering with phase information. It offers quantitative visualization of the refractive index and thickness distribution of weak absorption samples, which plays a vital role in the pathophysiology of various diseases and the characterization of various materials. It provides a possibility to bridge the gap between the imaging and scattering disciplines. The propagation of wavefront is described by the complex amplitude. The complex-value in the complex-domain is reconstructed from the intensity-value measurement by camera in the real-domain. Here, we regard the process of holographic recording and reconstruction as a transformation between complex-domain and real-domain, and discuss the mathematics and physical principles of reconstruction. We review the DH in underlying principles, technical approaches, and the breadth of applications. We conclude with emerging challenges and opportunities based on combining holographic imaging with other methodologies that expand the scope and utility of holographic imaging even further. The multidisciplinary nature brings technology and application experts together in label-free cell biology, analytical chemistry, clinical sciences, wavefront sensing, and semiconductor production.
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Affiliation(s)
- Zhengzhong Huang
- Department of Precision Instrument, Tsinghua University, Beijing, 100084, China
| | - Liangcai Cao
- Department of Precision Instrument, Tsinghua University, Beijing, 100084, China.
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Raj P, Paidi SK, Conway L, Chatterjee A, Barman I. CellSNAP: a fast, accurate algorithm for 3D cell segmentation in quantitative phase imaging. JOURNAL OF BIOMEDICAL OPTICS 2024; 29:S22706. [PMID: 38638450 PMCID: PMC11025678 DOI: 10.1117/1.jbo.29.s2.s22706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 03/22/2024] [Accepted: 03/28/2024] [Indexed: 04/20/2024]
Abstract
Significance Three-dimensional quantitative phase imaging (QPI) has rapidly emerged as a complementary tool to fluorescence imaging, as it provides an objective measure of cell morphology and dynamics, free of variability due to contrast agents. It has opened up new directions of investigation by providing systematic and correlative analysis of various cellular parameters without limitations of photobleaching and phototoxicity. While current QPI systems allow the rapid acquisition of tomographic images, the pipeline to analyze these raw three-dimensional (3D) tomograms is not well-developed. We focus on a critical, yet often underappreciated, step of the analysis pipeline that of 3D cell segmentation from the acquired tomograms. Aim We report the CellSNAP (Cell Segmentation via Novel Algorithm for Phase Imaging) algorithm for the 3D segmentation of QPI images. Approach The cell segmentation algorithm mimics the gemstone extraction process, initiating with a coarse 3D extrusion from a two-dimensional (2D) segmented mask to outline the cell structure. A 2D image is generated, and a segmentation algorithm identifies the boundary in the x - y plane. Leveraging cell continuity in consecutive z -stacks, a refined 3D segmentation, akin to fine chiseling in gemstone carving, completes the process. Results The CellSNAP algorithm outstrips the current gold standard in terms of speed, robustness, and implementation, achieving cell segmentation under 2 s per cell on a single-core processor. The implementation of CellSNAP can easily be parallelized on a multi-core system for further speed improvements. For the cases where segmentation is possible with the existing standard method, our algorithm displays an average difference of 5% for dry mass and 8% for volume measurements. We also show that CellSNAP can handle challenging image datasets where cells are clumped and marred by interferogram drifts, which pose major difficulties for all QPI-focused AI-based segmentation tools. Conclusion Our proposed method is less memory intensive and significantly faster than existing methods. The method can be easily implemented on a student laptop. Since the approach is rule-based, there is no need to collect a lot of imaging data and manually annotate them to perform machine learning based training of the model. We envision our work will lead to broader adoption of QPI imaging for high-throughput analysis, which has, in part, been stymied by a lack of suitable image segmentation tools.
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Affiliation(s)
- Piyush Raj
- Johns Hopkins University, Department of Mechanical Engineering, Baltimore, Maryland, United States
| | - Santosh Kumar Paidi
- Johns Hopkins University, Department of Mechanical Engineering, Baltimore, Maryland, United States
| | - Lauren Conway
- Johns Hopkins University, Department of Chemical and Biomolecular Engineering, Baltimore, Maryland, United States
| | - Arnab Chatterjee
- Johns Hopkins University, Department of Mechanical Engineering, Baltimore, Maryland, United States
| | - Ishan Barman
- Johns Hopkins University, Department of Mechanical Engineering, Baltimore, Maryland, United States
- The Johns Hopkins University, School of Medicine, The Russell H. Morgan Department of Radiology and Radiological Science, Baltimore, Maryland, United States
- Johns Hopkins University, Department of Oncology, Baltimore, Maryland, United States
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Liu R, Wen K, Li J, Ma Y, Zheng J, An S, Min J, Zalevsky Z, Yao B, Gao P. Multi-harmonic structured illumination-based optical diffraction tomography. APPLIED OPTICS 2023; 62:9199-9206. [PMID: 38108690 DOI: 10.1364/ao.508138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 11/08/2023] [Indexed: 12/19/2023]
Abstract
Imaging speed and spatial resolution are key factors in optical diffraction tomography (ODT), while they are mutually exclusive in 3D refractive index imaging. This paper presents a multi-harmonic structured illumination-based optical diffraction tomography (MHSI-ODT) to acquire 3D refractive index (RI) maps of transparent samples. MHSI-ODT utilizes a digital micromirror device (DMD) to generate structured illumination containing multiple harmonics. For each structured illumination orientation, four spherical spectral crowns are solved from five phase-shifted holograms, meaning that the acquisition of each spectral crown costs 1.25 raw images. Compared to conventional SI-ODT, which retrieves two spectral crowns from three phase-shifted raw images, MHSI-ODT enhances the imaging speed by 16.7% in 3D RI imaging. Meanwhile, MHSI-ODT exploits both the 1st-order and the 2nd-order harmonics; therefore, it has a better intensity utilization of structured illumination. We demonstrated the performance of MHSI-ODT by rendering the 3D RI distributions of 5 µm polystyrene (PS) microspheres and biological samples.
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Aleksandrovych M, Strassberg M, Melamed J, Xu M. Polarization differential interference contrast microscopy with physics-inspired plug-and-play denoiser for single-shot high-performance quantitative phase imaging. BIOMEDICAL OPTICS EXPRESS 2023; 14:5833-5850. [PMID: 38021115 PMCID: PMC10659786 DOI: 10.1364/boe.499316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 08/31/2023] [Accepted: 09/15/2023] [Indexed: 12/01/2023]
Abstract
We present single-shot high-performance quantitative phase imaging with a physics-inspired plug-and-play denoiser for polarization differential interference contrast (PDIC) microscopy. The quantitative phase is recovered by the alternating direction method of multipliers (ADMM), balancing total variance regularization and a pre-trained dense residual U-net (DRUNet) denoiser. The custom DRUNet uses the Tanh activation function to guarantee the symmetry requirement for phase retrieval. In addition, we introduce an adaptive strategy accelerating convergence and explicitly incorporating measurement noise. After validating this deep denoiser-enhanced PDIC microscopy on simulated data and phantom experiments, we demonstrated high-performance phase imaging of histological tissue sections. The phase retrieval by the denoiser-enhanced PDIC microscopy achieves significantly higher quality and accuracy than the solution based on Fourier transforms or the iterative solution with total variance regularization alone.
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Affiliation(s)
- Mariia Aleksandrovych
- Dept. of Physics and Astronomy, Hunter College and the Graduate Center, The City University of New York, 695 Park Ave, New York, NY 10065, USA
| | - Mark Strassberg
- Dept. of Physics and Astronomy, Hunter College and the Graduate Center, The City University of New York, 695 Park Ave, New York, NY 10065, USA
| | - Jonathan Melamed
- Department of Pathology, New York University Langone School of Medicine, New York, NY 10016, USA
| | - Min Xu
- Dept. of Physics and Astronomy, Hunter College and the Graduate Center, The City University of New York, 695 Park Ave, New York, NY 10065, USA
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Raj P, Paidi S, Conway L, Chatterjee A, Barman I. CellSNAP: A fast, accurate algorithm for 3D cell segmentation in quantitative phase imaging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.24.550376. [PMID: 37546926 PMCID: PMC10402093 DOI: 10.1101/2023.07.24.550376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Quantitative phase imaging (QPI) has rapidly emerged as a complementary tool to fluorescence imaging, as it provides an objective measure of cell morphology and dynamics, free of variability due to contrast agents. In particular, three-dimensional (3D) tomographic imaging of live cells has opened up new directions of investigation by providing systematic and correlative analysis of various cellular parameters without limitations of photobleaching and phototoxicity. While current QPI systems allow the rapid acquisition of tomographic images, the pipeline to analyze these raw 3D tomograms is not well-developed. This work focuses on a critical, yet often underappreciated, step of the analysis pipeline, that of 3D cell segmentation from the acquired tomograms. The current method employed for such tasks is the Otsu-based 3D watershed algorithm, which works well for isolated cells; however, it is very challenging to draw boundaries when the cells are clumped. This process is also memory intensive since the processing requires computation on a 3D stack of images. We report the CellSNAP (Cell Segmentation via Novel Algorithm for Phase Imaging) algorithm for the segmentation of QPI images, which outstrips the current gold standard in terms of speed, robustness, and implementation, achieving cell segmentation under 2 seconds per cell on a single-core processor. The implementation of CellSNAP can easily be parallelized on a multi-core system for further speed improvements. For the cases where segmentation is possible with the existing standard method, our algorithm displays an average difference of 5% for dry mass and 8% for volume measurements. We also show that CellSNAP can handle challenging image datasets where cells are clumped and marred by interferogram drifts, which pose major difficulties for all QPI-focused segmentation tools. We envision our work will lead to the broader adoption of QPI imaging for high-throughput analysis, which has, in part, been stymied by a lack of suitable image segmentation tools.
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Affiliation(s)
- Piyush Raj
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Santosh Paidi
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Lauren Conway
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Arnab Chatterjee
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Ishan Barman
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University, School of Medicine, Baltimore, Maryland, USA
- Department of Oncology, Johns Hopkins University, Baltimore, Maryland, USA
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Ullah H, Li J, Zhou S, Bai Z, Ye R, Chen Q, Zuo C. Parallel synthetic aperture transport-of-intensity diffraction tomography with annular illumination. OPTICS LETTERS 2023; 48:1638-1641. [PMID: 37221729 DOI: 10.1364/ol.485406] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 02/21/2023] [Indexed: 05/25/2023]
Abstract
Transport-of-intensity diffraction tomography (TIDT) is a recently developed label-free computational microscopy technique that retrieves high-resolution three-dimensional (3D) refractive index (RI) distribution of biological specimens from 3D intensity-only measurements. However, the non-interferometric synthetic aperture in TIDT is generally achieved sequentially through the acquisition of a large number of through-focus intensity stacks captured at different illumination angles, resulting in a very cumbersome and redundant data acquisition process. To this end, we present a parallel implementation of a synthetic aperture in TIDT (PSA-TIDT) with annular illumination. We found that the matched annular illumination provides a mirror-symmetric 3D optical transfer function, indicating the analyticity in the upper half-plane of the complex phase function, which allows for recovery of the 3D RI from a single intensity stack. We experimentally validated PSA-TIDT by conducting high-resolution tomographic imaging of various unlabeled biological samples, including human breast cancer cell lines (MCF-7), human hepatocyte carcinoma cell lines (HepG2), Henrietta Lacks (HeLa) cells, and red blood cells (RBCs).
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Roadmap on Digital Holography-Based Quantitative Phase Imaging. J Imaging 2021; 7:jimaging7120252. [PMID: 34940719 PMCID: PMC8703719 DOI: 10.3390/jimaging7120252] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 11/11/2021] [Accepted: 11/15/2021] [Indexed: 12/02/2022] Open
Abstract
Quantitative Phase Imaging (QPI) provides unique means for the imaging of biological or technical microstructures, merging beneficial features identified with microscopy, interferometry, holography, and numerical computations. This roadmap article reviews several digital holography-based QPI approaches developed by prominent research groups. It also briefly discusses the present and future perspectives of 2D and 3D QPI research based on digital holographic microscopy, holographic tomography, and their applications.
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Wen K, Gao Z, Fang X, Liu M, Zheng J, Ma Y, Zalevsky Z, Gao P. Structured illumination microscopy with partially coherent illumination for phase and fluorescent imaging. OPTICS EXPRESS 2021; 29:33679-33693. [PMID: 34809175 DOI: 10.1364/oe.435783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 09/23/2021] [Indexed: 06/13/2023]
Abstract
This study presents a partially coherent illumination based (PCI-based) SIM apparatus for dual-modality (phase and fluorescent) microscopic imaging. The partially coherent illumination (PCI) is generated by placing a rotating diffuser on a monochromatic laser beam, which suppresses speckle noise in the dual-modality images and endows the apparatus with sound sectioning capability. With this system, label-free quantitative phase and super-resolved/sectioned fluorescent images can be obtained for the same sample. We have demonstrated the superiority of the system in phase imaging of transparent cells with high endogenous contrast and in a quantitative manner. In the meantime, we have also demonstrated fluorescent imaging of fluorescent beads, rat tail crosscut, wheat anther, and hibiscus pollen with super-resolution and optical sectioning. We envisage that the proposed method can be applied to many fields, including but not limited to biomedical, industrial, chemistry fields.
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Xiao Y, Wei S, Xue S, Kuang C, Yang A, Wei M, Lin H, Zhou R. High-speed Fourier ptychographic microscopy for quantitative phase imaging. OPTICS LETTERS 2021; 46:4785-4788. [PMID: 34598199 DOI: 10.1364/ol.428731] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 08/10/2021] [Indexed: 06/13/2023]
Abstract
Fourier ptychographic microscopy (FPM), as an emerging computational imaging method, has been applied to quantitative phase imaging with resolution bypassing the physical limit of the detection objective. Due to the weak illumination intensity and long image acquisition time, the achieved imaging speed in current FPM methods is still low, making them unsuitable for real-time imaging applications. We propose and demonstrate a high-speed FPM method based on using laser illumination and digital micro-mirror devices for illumination angle scanning. In this new, to the best of our knowledge, FPM method, we realized quantitative phase imaging and intensity imaging at over 42 frames per second (fps) with around 1 µm lateral resolution. The quantitative phase images have revealed membrane height fluctuations of red blood cells with nanometer-scale sensitivity, while the intensity images have resolved subcellular features in stained cancer tissue slices.
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Pirone D, Mugnano M, Memmolo P, Merola F, Lama GC, Castaldo R, Miccio L, Bianco V, Grilli S, Ferraro P. Three-Dimensional Quantitative Intracellular Visualization of Graphene Oxide Nanoparticles by Tomographic Flow Cytometry. NANO LETTERS 2021; 21:5958-5966. [PMID: 34232045 PMCID: PMC9297328 DOI: 10.1021/acs.nanolett.1c00868] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Interaction of nanoparticles (NPs) with cells is of fundamental importance in biology and biomedical sciences. NPs can be taken up by cells, thus interacting with their intracellular elements, modifying the life cycle pathways, and possibly inducing death. Therefore, there is a great interest in understanding and visualizing the process of cellular uptake itself or even secondary effects, for example, toxicity. Nowadays, no method is reported yet in which 3D imaging of NPs distribution can be achieved for suspended cells in flow-cytometry. Here we show that, by means of label-free tomographic flow-cytometry, it is possible to obtain full 3D quantitative spatial distribution of nanographene oxide (nGO) inside each single flowing cell. This can allow the setting of a class of biomarkers that characterize the 3D spatial intracellular deployment of nGO or other NPs clusters, thus opening the route for quantitative descriptions to discover new insights in the realm of NP-cell interactions.
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Affiliation(s)
- Daniele Pirone
- Institute
of Applied Sciences and Intelligent Systems “E. Caianiello”, CNR-ISASI, Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy
- Department
of Electrical Engineering and Information Technologies (DIETI), University of Naples “Federico II”, via Claudio 21, 80125 Napoli, Italy
| | - Martina Mugnano
- Institute
of Applied Sciences and Intelligent Systems “E. Caianiello”, CNR-ISASI, Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy
| | - Pasquale Memmolo
- Institute
of Applied Sciences and Intelligent Systems “E. Caianiello”, CNR-ISASI, Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy
| | - Francesco Merola
- Institute
of Applied Sciences and Intelligent Systems “E. Caianiello”, CNR-ISASI, Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy
| | - Giuseppe Cesare Lama
- Institute
of Polymers, Composites and Biomaterials, CNR-IPCB, Via Campi
Flegrei 34, 80078 Pozzuoli, Napoli, Italy
| | - Rachele Castaldo
- Institute
of Polymers, Composites and Biomaterials, CNR-IPCB, Via Campi
Flegrei 34, 80078 Pozzuoli, Napoli, Italy
| | - Lisa Miccio
- Institute
of Applied Sciences and Intelligent Systems “E. Caianiello”, CNR-ISASI, Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy
| | - Vittorio Bianco
- Institute
of Applied Sciences and Intelligent Systems “E. Caianiello”, CNR-ISASI, Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy
| | - Simonetta Grilli
- Institute
of Applied Sciences and Intelligent Systems “E. Caianiello”, CNR-ISASI, Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy
| | - Pietro Ferraro
- Institute
of Applied Sciences and Intelligent Systems “E. Caianiello”, CNR-ISASI, Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy
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