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Park J, Bai B, Ryu D, Liu T, Lee C, Luo Y, Lee MJ, Huang L, Shin J, Zhang Y, Ryu D, Li Y, Kim G, Min HS, Ozcan A, Park Y. Artificial intelligence-enabled quantitative phase imaging methods for life sciences. Nat Methods 2023; 20:1645-1660. [PMID: 37872244 DOI: 10.1038/s41592-023-02041-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Accepted: 09/11/2023] [Indexed: 10/25/2023]
Abstract
Quantitative phase imaging, integrated with artificial intelligence, allows for the rapid and label-free investigation of the physiology and pathology of biological systems. This review presents the principles of various two-dimensional and three-dimensional label-free phase imaging techniques that exploit refractive index as an intrinsic optical imaging contrast. In particular, we discuss artificial intelligence-based analysis methodologies for biomedical studies including image enhancement, segmentation of cellular or subcellular structures, classification of types of biological samples and image translation to furnish subcellular and histochemical information from label-free phase images. We also discuss the advantages and challenges of artificial intelligence-enabled quantitative phase imaging analyses, summarize recent notable applications in the life sciences, and cover the potential of this field for basic and industrial research in the life sciences.
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Affiliation(s)
- Juyeon Park
- Department of Physics, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
- KAIST Institute for Health Science and Technology, KAIST, Daejeon, Republic of Korea
| | - Bijie Bai
- Electrical and Computer Engineering Department, University of California, Los Angeles, Los Angeles, CA, USA
- Bioengineering Department, University of California, Los Angeles, Los Angeles, CA, USA
| | - DongHun Ryu
- Department of Physics, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
- KAIST Institute for Health Science and Technology, KAIST, Daejeon, Republic of Korea
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Tairan Liu
- Electrical and Computer Engineering Department, University of California, Los Angeles, Los Angeles, CA, USA
| | - Chungha Lee
- Department of Physics, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
- KAIST Institute for Health Science and Technology, KAIST, Daejeon, Republic of Korea
| | - Yi Luo
- Electrical and Computer Engineering Department, University of California, Los Angeles, Los Angeles, CA, USA
| | - Mahn Jae Lee
- KAIST Institute for Health Science and Technology, KAIST, Daejeon, Republic of Korea
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Luzhe Huang
- Electrical and Computer Engineering Department, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jeongwon Shin
- KAIST Institute for Health Science and Technology, KAIST, Daejeon, Republic of Korea
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Yijie Zhang
- Electrical and Computer Engineering Department, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Yuzhu Li
- Electrical and Computer Engineering Department, University of California, Los Angeles, Los Angeles, CA, USA
| | - Geon Kim
- Department of Physics, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
- KAIST Institute for Health Science and Technology, KAIST, Daejeon, Republic of Korea
| | | | - Aydogan Ozcan
- Electrical and Computer Engineering Department, University of California, Los Angeles, Los Angeles, CA, USA.
- Bioengineering Department, University of California, Los Angeles, Los Angeles, CA, USA.
| | - YongKeun Park
- Department of Physics, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
- KAIST Institute for Health Science and Technology, KAIST, Daejeon, Republic of Korea.
- Tomocube, Daejeon, Republic of Korea.
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Li G, Zhang R, Wei M, Yin C, Sun J, Zhang Y. Lensfree Diffraction Reconstruction Approach Enables Early Detection of Cancer In Vitro Based on Molecular Diagnosis. ACS Sens 2020; 5:3091-3098. [PMID: 32677430 DOI: 10.1021/acssensors.0c00990] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Before there are any megascopic cancer clinical symptoms, molecular diagnosis is the main method for detecting cancer-associated gene and tumor marker. The existing detection facilities are all expensive, complicated to operate, and time-consuming, thereby making them difficult to popularize and benefit humans. In this study, we proposed a high-throughput and cost-effective approach, which enables accurate detection of extremely rare cancer cells based on molecular diagnosis of target tumor marker and a lensfree diffraction imaging platform. This approach achieves high-speed and high-quality reconstruction of huge images, which well solves the problem that precise recognition is almost impossible utilizing raw image because of significant pattern magnification and serious overlaps. Furthermore, the cells which are labeled with immune microbeads can be screened using the determined covered pixel sets, which are extracted in different focus reconstruction planes. The recognition strategy is implemented based on set intersection. With this method, the target cancer cells can be rapidly and accurately screened in a large number of benign cell samples. Besides, the detection equipment is cost-effective and easy to operate and popularize. It is expected to be widely used as a diagnostic tool for early detection of cancer.
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Affiliation(s)
- Guoxiao Li
- School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, China
| | - Rongbiao Zhang
- School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, China
| | - Mingji Wei
- School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, China
| | - Changsheng Yin
- Institute of Life Sciences, Jiangsu University, Zhenjiang, Jiangsu 212013, China
| | - Jian Sun
- School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, China
| | - Yecheng Zhang
- School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, China
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Zhang H, Wang W, Liu C, Liu J. Pixel super-resolved lens-free on-chip microscopy based on dual laterally shifting modulation. APPLIED OPTICS 2020; 59:3411-3416. [PMID: 32400453 DOI: 10.1364/ao.387428] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Accepted: 03/11/2020] [Indexed: 06/11/2023]
Abstract
Achieving high spatial resolution over a wide field of view (FOV) is the goal of many imaging systems. In a traditional lens-based microscope, designing a complex objective with high numerical aperture (NA) to achieve this goal is a tough and challenging task. The lens-free wide-field imaging method based on phase retrieval provides a new way to bypass the trade-off between the spatial resolution and FOV of conventional microscopy. However, the typical lens-free microscopy usually requires mechanical devices with high precision and repeatability. In this paper, we report a robust and cost-effective pixel super-resolved lens-free imaging method based on dual laterally shifting modulation. A thin diffuser is inserted between the object and the image sensor to be used as the modulator. The diffuser and the object are transversely scanned at the same time to add diversities for phase retrieval and pixel super-resolution, respectively. In this way, the positional shifts of the diffuser and the object can be directly recovered with the registration algorithm, thus addressing the low stability and inaccuracy issues of translation stages. We also propose a pixel super-resolution phase-retrieval algorithm to recover the object and the unknown diffuser. We first use numerical simulations to evaluate the proposed scheme. Then, we validate this approach by imaging a resolution target and a pollen sample, thus achieving an FOV of ${\sim}{30}\;{\text{mm}^2}$∼30mm2 and a half-pitch resolution of 0.78 µm, which surpasses 2.14 times the theoretical Nyquist-Shannon sampling resolution limit. Finally, the 3D refocusing ability is also verified by imaging a thick mosquito sample.
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Wang J, Yu X, Wang Y, Pan X, Li D. Detection of viability of micro-algae cells by optofluidic hologram pattern. BIOMICROFLUIDICS 2018; 12:024111. [PMID: 29657655 PMCID: PMC5876039 DOI: 10.1063/1.5021179] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2018] [Accepted: 03/16/2018] [Indexed: 06/08/2023]
Abstract
A rapid detection of micro-algae activity is critical for analysis of ship ballast water. A new method for detecting micro-algae activity based on lens-free optofluidic holographic imaging is presented in this paper. A compact lens-free optofluidic holographic imaging device was developed. This device is mainly composed of a light source, a small through-hole, a light propagation module, a microfluidic chip, and an image acquisition and processing module. The excited light from the light source passes through a small hole to reach the surface of the micro-algae cells in the microfluidic chip, and a holographic image is formed by the diffraction light of surface of micro-algae cells. The relation between the characteristics in the hologram pattern and the activity of micro-algae cells was investigated by using this device. The characteristics of the hologram pattern were extracted to represent the activity of micro-algae cells. To demonstrate the accuracy of the presented method and device, four species of micro-algae cells were employed as the test samples and the comparison experiments between the alive and dead cells of four species of micro-algae were conducted. The results show that the developed method and device can determine live/dead microalgae cells accurately.
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Affiliation(s)
- Junsheng Wang
- College of Information and Science Technology, Dalian Maritime University, Dalian 116026, China
| | - Xiaomei Yu
- College of Information and Science Technology, Dalian Maritime University, Dalian 116026, China
| | - Yanjuan Wang
- College of Information and Science Technology, Dalian Maritime University, Dalian 116026, China
| | - Xinxiang Pan
- College of Marine Engineering, Dalian Maritime University, Dalian 116026, China
| | - Dongqing Li
- Department of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, Ontario N2L3G1, Canada
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Garcia-Sucerquia J. Color digital lensless holographic microscopy: laser versus LED illumination. APPLIED OPTICS 2016; 55:6649-6655. [PMID: 27556985 DOI: 10.1364/ao.55.006649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
A comparison of the performance of color digital lensless holographic microscopy (CDLHM) as utilized for illumination of RGB lasers or a super-bright white-light LED with a set of spectral filters is presented. As the use of lasers in CDLHM conceals the possibility of having a compact, lightweight, portable, and low cost microscope, and additionally the limited available laser radiation wavelengths limit a real multispectral imaging microscope, here we present the use of super-bright white-light LED and spectral filters for illuminating the sample. The performance of RGB laser-CDLHM and LED-CDLHM is evaluated on imaging a section of the head of a Drosophila melanogaster fly. This comparison shows that there is trade-off between the spatial resolution of the microscope and the light sources utilized, which can be understood with regard to the coherence properties of the illuminating light. Despite the smaller spatial coherence features of LED-CDLHM in comparison with laser-CDLHM, the former shows promise as a portable RGB digital lensless holographic microscope that could be extended to other wavelengths by the use of different spectral filters.
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Feng S, Wang M, Wu J. Lensless in-line holographic microscope with Talbot grating illumination. OPTICS LETTERS 2016; 41:3157-3160. [PMID: 27420484 DOI: 10.1364/ol.41.003157] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
We have developed a wide field-of-view lensless in-line holographic microscope (LIHM) capable of acquiring microscopic images with a compact design. In our imaging system, a Ronchi grating was illuminated by a collimated laser beam to generate a Talbot self-imaging grating illumination on the sample, and the in-line holograms were recorded by a CMOS imaging sensor behind the sample. An iterative reconstruction algorithm was then applied to reconstruct the sample image while eliminating the twin-image background that appears in traditional in-line holography. In the algorithm, the dark areas of the illumination grating were used as a known constraint to define the sample support that led to convergence of the iteration. The whole-sample image can be acquired by laterally shifting the grating. We demonstrated the performance of our iteration algorithm and imaging system by successfully acquiring images of polystyrene microspheres with 5 μm diameter and the wing of a green lacewing.
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McLeod E, Ozcan A. Unconventional methods of imaging: computational microscopy and compact implementations. REPORTS ON PROGRESS IN PHYSICS. PHYSICAL SOCIETY (GREAT BRITAIN) 2016; 79:076001. [PMID: 27214407 DOI: 10.1088/0034-4885/79/7/076001] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
In the past two decades or so, there has been a renaissance of optical microscopy research and development. Much work has been done in an effort to improve the resolution and sensitivity of microscopes, while at the same time to introduce new imaging modalities, and make existing imaging systems more efficient and more accessible. In this review, we look at two particular aspects of this renaissance: computational imaging techniques and compact imaging platforms. In many cases, these aspects go hand-in-hand because the use of computational techniques can simplify the demands placed on optical hardware in obtaining a desired imaging performance. In the first main section, we cover lens-based computational imaging, in particular, light-field microscopy, structured illumination, synthetic aperture, Fourier ptychography, and compressive imaging. In the second main section, we review lensfree holographic on-chip imaging, including how images are reconstructed, phase recovery techniques, and integration with smart substrates for more advanced imaging tasks. In the third main section we describe how these and other microscopy modalities have been implemented in compact and field-portable devices, often based around smartphones. Finally, we conclude with some comments about opportunities and demand for better results, and where we believe the field is heading.
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Affiliation(s)
- Euan McLeod
- College of Optical Sciences, University of Arizona, Tucson, AZ 85721, USA
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PicoMolar level detection of protein biomarkers based on electronic sizing of bead aggregates: theoretical and experimental considerations. Biomed Microdevices 2016; 17:119. [PMID: 26589228 DOI: 10.1007/s10544-015-0022-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
We demonstrate a novel method for electronically detecting and quantifying protein biomarkers using microfluidic impedance cytometry. Our biosensor, which consists of gold electrodes micro-fabricated in a microchannel, detects the differences between bead aggregates of varying sizes in a micro-pore sandwiched between two micro channels. We perform a sandwich immunoassay, where the complementary antibody pairs are immobilized on two different bead types, and the presence of antigen results in bead aggregation, the amount of which depends on antigen quantity. When single beads or bead aggregates pass through the impedance sensor, differences in impedance change are detected. In this manuscript, we perform a comprehensive theoretical study on the limits imposed on sensitivity of this technique due to electronic noise and also mass transfer and reaction limits. We also experimentally characterize the performance of this technique by validating the technique on an IgG detection assay. A detection limit at the picoMolar level is demonstrated, thus comparable in sensitivity to a sandwich ELISA.
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Abstract
High-resolution optical microscopy has traditionally relied on high-magnification and high-numerical aperture objective lenses. In contrast, lensless microscopy can provide high-resolution images without the use of any focusing lenses, offering the advantages of a large field of view, high resolution, cost-effectiveness, portability, and depth-resolved three-dimensional (3D) imaging. Here we review various approaches to lensless imaging, as well as its applications in biosensing, diagnostics, and cytometry. These approaches include shadow imaging, fluorescence, holography, superresolution 3D imaging, iterative phase recovery, and color imaging. These approaches share a reliance on computational techniques, which are typically necessary to reconstruct meaningful images from the raw data captured by digital image sensors. When these approaches are combined with physical innovations in sample preparation and fabrication, lensless imaging can be used to image and sense cells, viruses, nanoparticles, and biomolecules. We conclude by discussing several ways in which lensless imaging and sensing might develop in the near future.
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Affiliation(s)
- Aydogan Ozcan
- Department of Electrical Engineering.,Department of Bioengineering, and.,California NanoSystems Institute, University of California, Los Angeles, California 90095;
| | - Euan McLeod
- College of Optical Sciences, University of Arizona, Tucson, Arizona 85721;
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Rodrigo JA, Alieva T. Rapid quantitative phase imaging for partially coherent light microscopy. OPTICS EXPRESS 2014; 22:13472-83. [PMID: 24921541 DOI: 10.1364/oe.22.013472] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
Partially coherent light provides promising advantages for imaging applications. In contrast to its completely coherent counterpart, it prevents image degradation due to speckle noise and decreases cross-talk among the imaged objects. These facts make attractive the partially coherent illumination for accurate quantitative imaging in microscopy. In this work, we present a non-interferometric technique and system for quantitative phase imaging with simultaneous determination of the spatial coherence properties of the sample illumination. Its performance is experimentally demonstrated in several examples underlining the benefits of partial coherence for practical imagining applications. The programmable optical setup comprises an electrically tunable lens and sCMOS camera that allows for high-speed measurement in the millisecond range.
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Wei Q, McLeod E, Qi H, Wan Z, Sun R, Ozcan A. On-chip cytometry using plasmonic nanoparticle enhanced lensfree holography. Sci Rep 2013; 3:1699. [PMID: 23608952 PMCID: PMC3632884 DOI: 10.1038/srep01699] [Citation(s) in RCA: 63] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2013] [Accepted: 04/05/2013] [Indexed: 12/21/2022] Open
Abstract
Computational microscopy tools, in particular lensfree on-chip imaging, provide a large field-of-view along with a long depth-of-field, which makes it feasible to rapidly analyze large volumes of specimen using a compact and light-weight on-chip imaging architecture. To bring molecular specificity to this high-throughput platform, here we demonstrate the use of plasmon-resonant metallic nanoparticles to automatically recognize different cell types based on their plasmon-enhanced lensfree holograms, detected and reconstructed over a large field-of-view of e.g., ~24 mm2.
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Affiliation(s)
- Qingshan Wei
- Electrical Engineering Department, University of California, Los Angeles, CA 90095, USA
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Mendoza-Yero O, Calabuig A, Tajahuerce E, Lancis J, Andrés P, Garcia-Sucerquia J. Femtosecond digital lensless holographic microscopy to image biological samples. OPTICS LETTERS 2013; 38:3205-3207. [PMID: 23988914 DOI: 10.1364/ol.38.003205] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
The use of femtosecond laser radiation in digital lensless holographic microscopy (DLHM) to image biological samples is presented. A mode-locked Ti:Sa laser that emits ultrashort pulses of 12 fs intensity FWHM, with 800 nm mean wavelength, at 75 MHz repetition rate is used as a light source. For comparison purposes, the light from a light-emitting diode is also used. A section of the head of a drosophila melanogaster fly is studied with both light sources. The experimental results show very different effects of the pinhole size on the spatial resolution with DLHM. Unaware phenomena on the field of the DLHM are analyzed.
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Affiliation(s)
- Omel Mendoza-Yero
- Institut de Noves Tecnologies de la Imatge (INIT), Universitat Jaume I, 12071 Castelló, Spain
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