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Liu Y, Uttam S. Perspective on quantitative phase imaging to improve precision cancer medicine. JOURNAL OF BIOMEDICAL OPTICS 2024; 29:S22705. [PMID: 38584967 PMCID: PMC10996848 DOI: 10.1117/1.jbo.29.s2.s22705] [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: 11/29/2023] [Revised: 03/03/2024] [Accepted: 03/15/2024] [Indexed: 04/09/2024]
Abstract
Significance Quantitative phase imaging (QPI) offers a label-free approach to non-invasively characterize cellular processes by exploiting their refractive index based intrinsic contrast. QPI captures this contrast by translating refractive index associated phase shifts into intensity-based quantifiable data with nanoscale sensitivity. It holds significant potential for advancing precision cancer medicine by providing quantitative characterization of the biophysical properties of cells and tissue in their natural states. Aim This perspective aims to discuss the potential of QPI to increase our understanding of cancer development and its response to therapeutics. It also explores new developments in QPI methods towards advancing personalized cancer therapy and early detection. Approach We begin by detailing the technical advancements of QPI, examining its implementations across transmission and reflection geometries and phase retrieval methods, both interferometric and non-interferometric. The focus then shifts to QPI's applications in cancer research, including dynamic cell mass imaging for drug response assessment, cancer risk stratification, and in-vivo tissue imaging. Results QPI has emerged as a crucial tool in precision cancer medicine, offering insights into tumor biology and treatment efficacy. Its sensitivity to detecting nanoscale changes holds promise for enhancing cancer diagnostics, risk assessment, and prognostication. The future of QPI is envisioned in its integration with artificial intelligence, morpho-dynamics, and spatial biology, broadening its impact in cancer research. Conclusions QPI presents significant potential in advancing precision cancer medicine and redefining our approach to cancer diagnosis, monitoring, and treatment. Future directions include harnessing high-throughput dynamic imaging, 3D QPI for realistic tumor models, and combining artificial intelligence with multi-omics data to extend QPI's capabilities. As a result, QPI stands at the forefront of cancer research and clinical application in cancer care.
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Affiliation(s)
- Yang Liu
- University of Illinois Urbana-Champaign, Beckman Institute for Advanced Science and Technology, Cancer Center at Illinois, Department of Bioengineering, Department of Electrical and Computer Engineering, Urbana, Illinois, United States
- University of Pittsburgh, Departments of Medicine and Bioengineering, Pittsburgh, Pennsylvania, United States
| | - Shikhar Uttam
- University of Pittsburgh, Department of Computational and Systems Biology, Pittsburgh, Pennsylvania, United States
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2
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Martel PD, Zhang C, Linninger AA, Lesage F. Phase contrast reflectance confocal brain imaging at 1650 nm. JOURNAL OF BIOMEDICAL OPTICS 2024; 29:026501. [PMID: 38414657 PMCID: PMC10898133 DOI: 10.1117/1.jbo.29.2.026501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 01/03/2024] [Accepted: 02/05/2024] [Indexed: 02/29/2024]
Abstract
Significance The imaging depth of microscopy techniques is limited by the ability of light to penetrate biological tissue. Recent research has addressed this limitation by combining a reflectance confocal microscope with the NIR-II (or shortwave infrared) spectrum. This approach offers significant imaging depth, is straightforward in design, and remains cost-effective. However, the imaging system, which relies on intrinsic signals, could benefit from adjustments in its optical design and post-processing methods to differentiate cortical cells, such as neurons and small blood vessels. Aim We implemented a phase contrast detection scheme to a reflectance confocal microscope using NIR-II spectral range as illumination. Approach We analyzed the features retrieved in the images while testing the imaging depth. Moreover, we introduce an acquisition method for distinguishing dynamic signals from the background, allowing the creation of vascular maps similar to those produced by optical coherence tomography. Results The phase contrast implementation is successful to retrieve deep images in the cortex up to 800 μ m using a cranial window. Vascular maps were retrieved at similar cortical depth and the possibility of combining multiple images can provide a vessel network. Conclusions Phase contrast reflectance confocal microscopy can improve the outlining of cortical cell bodies. With the presented framework, angiograms can be retrieved from the dynamic signal in the biological tissue. Our work presents an optical implementation and analysis techniques from a former microscope design.
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Affiliation(s)
- Patrick Delafontaine Martel
- Polytechnique Montreal, Department of Electrical Engineering, Montreal, Québec, Canada
- Montreal Heart Institute, Research Center, Montreal, Québec, Canada
| | - Cong Zhang
- Polytechnique Montreal, Department of Electrical Engineering, Montreal, Québec, Canada
- Montreal Heart Institute, Research Center, Montreal, Québec, Canada
| | - Andreas A Linninger
- University of Illinois, Department of Biomedical Engineering and Neurosurgery, Chicago, Illinois, United States
| | - Frédéric Lesage
- Polytechnique Montreal, Department of Electrical Engineering, Montreal, Québec, Canada
- Montreal Heart Institute, Research Center, Montreal, Québec, Canada
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Ströhl F, Wolfson DL, Opstad IS, Hansen DH, Mao H, Ahluwalia BS. Label-free superior contrast with c-band ultra-violet extinction microscopy. LIGHT, SCIENCE & APPLICATIONS 2023; 12:56. [PMID: 36864022 PMCID: PMC9981877 DOI: 10.1038/s41377-023-01105-6] [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: 10/27/2022] [Revised: 02/14/2023] [Accepted: 02/14/2023] [Indexed: 06/18/2023]
Abstract
In 1934, Frits Zernike demonstrated that it is possible to exploit the sample's refractive index to obtain superior contrast images of biological cells. The refractive index contrast of a cell surrounded by media yields a change in the phase and intensity of the transmitted light wave. This change can be due to either scattering or absorption caused by the sample. Most cells are transparent at visible wavelengths, which means the imaginary component of their complex refractive index, also known as extinction coefficient k, is close to zero. Here, we explore the use of c-band ultra-violet (UVC) light for high-contrast high-resolution label-free microscopy, as k is naturally substantially higher in the UVC than at visible wavelengths. Using differential phase contrast illumination and associated processing, we achieve a 7- to 300-fold improvement in contrast compared to visible-wavelength and UVA differential interference contrast microscopy or holotomography, and quantify the extinction coefficient distribution within liver sinusoidal endothelial cells. With a resolution down to 215 nm, we are, for the first time in a far-field label-free method, able to image individual fenestrations within their sieve plates which normally requires electron or fluorescence superresolution microscopy. UVC illumination also matches the excitation peak of intrinsically fluorescent proteins and amino acids and thus allows us to utilize autofluorescence as an independent imaging modality on the same setup.
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Affiliation(s)
- Florian Ströhl
- Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway.
| | - Deanna L Wolfson
- Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway
| | - Ida S Opstad
- Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway
| | - Daniel H Hansen
- Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway
| | - Hong Mao
- Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway
| | - Balpreet S 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
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4
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Optical Diffraction Tomography Using Nearly In-Line Holography with a Broadband LED Source. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12030951] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
We present optical tomography methods for a 3D refractive index reconstruction of weakly scattering objects using LED light sources. We are able to record holograms by minimizing the optical path difference between the signal and reference beams while separating the scattered field from its twin image. We recorded multiple holograms by illuminating the LEDs sequentially and reconstructed the 3D refractive index reconstruction of the sample. The reconstructions show high signal-to-noise ratio in which the effect of speckle artifacts is highly minimized due to the partially incoherent illumination of the LEDs. Results from combining different illumination wavelengths are also described demonstrating higher acquisition speed.
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Park J, Brady DJ, Zheng G, Tian L, Gao L. Review of bio-optical imaging systems with a high space-bandwidth product. ADVANCED PHOTONICS 2021; 3:044001. [PMID: 35178513 PMCID: PMC8849623 DOI: 10.1117/1.ap.3.4.044001] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
Optical imaging has served as a primary method to collect information about biosystems across scales-from functionalities of tissues to morphological structures of cells and even at biomolecular levels. However, to adequately characterize a complex biosystem, an imaging system with a number of resolvable points, referred to as a space-bandwidth product (SBP), in excess of one billion is typically needed. Since a gigapixel-scale far exceeds the capacity of current optical imagers, compromises must be made to obtain either a low spatial resolution or a narrow field-of-view (FOV). The problem originates from constituent refractive optics-the larger the aperture, the more challenging the correction of lens aberrations. Therefore, it is impractical for a conventional optical imaging system to achieve an SBP over hundreds of millions. To address this unmet need, a variety of high-SBP imagers have emerged over the past decade, enabling an unprecedented resolution and FOV beyond the limit of conventional optics. We provide a comprehensive survey of high-SBP imaging techniques, exploring their underlying principles and applications in bioimaging.
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Affiliation(s)
- Jongchan Park
- University of California, Department of Bioengineering, Los Angeles, California, United States
| | - David J. Brady
- University of Arizona, James C. Wyant College of Optical Sciences, Tucson, Arizona, United States
| | - Guoan Zheng
- University of Connecticut, Department of Biomedical Engineering, Storrs, Connecticut, United States
- University of Connecticut, Department of Electrical and Computer Engineering, Storrs, Connecticut, United States
| | - Lei Tian
- Boston University, Department of Electrical and Computer Engineering, Boston, Massachusetts, United States
| | - Liang Gao
- University of California, Department of Bioengineering, Los Angeles, California, United States
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Chen X, Kandel ME, Popescu G. Spatial light interference microscopy: principle and applications to biomedicine. ADVANCES IN OPTICS AND PHOTONICS 2021; 13:353-425. [PMID: 35494404 PMCID: PMC9048520 DOI: 10.1364/aop.417837] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
In this paper, we review spatial light interference microscopy (SLIM), a common-path, phase-shifting interferometer, built onto a phase-contrast microscope, with white-light illumination. As one of the most sensitive quantitative phase imaging (QPI) methods, SLIM allows for speckle-free phase reconstruction with sub-nanometer path-length stability. We first review image formation in QPI, scattering, and full-field methods. Then, we outline SLIM imaging from theory and instrumentation to diffraction tomography. Zernike's phase-contrast microscopy, phase retrieval in SLIM, and halo removal algorithms are discussed. Next, we discuss the requirements for operation, with a focus on software developed in-house for SLIM that enables high-throughput acquisition, whole slide scanning, mosaic tile registration, and imaging with a color camera. We introduce two methods for solving the inverse problem using SLIM, white-light tomography, and Wolf phase tomography. Lastly, we review the applications of SLIM in basic science and clinical studies. SLIM can study cell dynamics, cell growth and proliferation, cell migration, mass transport, etc. In clinical settings, SLIM can assist with cancer studies, reproductive technology, blood testing, etc. Finally, we review an emerging trend, where SLIM imaging in conjunction with artificial intelligence brings computational specificity and, in turn, offers new solutions to outstanding challenges in cell biology and pathology.
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Fu R, Su Y, Wang R, Lin X, Jin X, Yang H, Du W, Shan X, Lv W, Huang G. Single cell capture, isolation, and long-term in-situ imaging using quantitative self-interference spectroscopy. Cytometry A 2021; 99:601-609. [PMID: 33704903 DOI: 10.1002/cyto.a.24333] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 03/04/2021] [Accepted: 03/05/2021] [Indexed: 11/09/2022]
Abstract
Single cell research with microfluidic chip is of vital importance in biomedical studies and clinical medicine. Simultaneous microfluidic cell manipulations and long-term cell monitoring needs further investigations due to the lack of label-free quantitative imaging techniques and systems. In this work, single cell capture, isolation and long-term in-situ monitoring was realized with a microfluidic cell chip, compact cell incubator and quantitative self-interference spectroscopy. The proposed imaging method could obtain quantitative and dynamic refractive index distribution in living cells. And the designed microfluidic chip could capture and isolate single cells. The customized incubator could support cell growth conditions when single cell was captured in microfluidic chip. According to the results, single cells could be trapped, transferred and pushed into the culture chamber with the microfluidic chip. The incubator could culture single cells in the chip for 120 h. The refractive index sensitivity of the proposed quantitative imaging method was 0.0282 and the relative error was merely 0.04%.
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Affiliation(s)
- Rongxin Fu
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Ya Su
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Ruliang Wang
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Xue Lin
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Xiangyu Jin
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Han Yang
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Wenli Du
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Xiaohui Shan
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Wenqi Lv
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Guoliang Huang
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China.,National Engineering Research Center for Beijing Biochip Technology, Beijing, China
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Ayoub AB, Lim J, Antoine EE, Psaltis D. 3D reconstruction of weakly scattering objects from 2D intensity-only measurements using the Wolf transform. OPTICS EXPRESS 2021; 29:3976-3984. [PMID: 33770986 DOI: 10.1364/oe.414543] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 01/12/2021] [Indexed: 06/12/2023]
Abstract
A new approach to optical diffraction tomography (ODT) based on intensity measurements is presented. By applying the Wolf transform directly to intensity measurements, we observed unexpected behavior in the 3D reconstruction of the sample. Such a reconstruction does not explicitly represent a quantitative measure of the refractive index of the sample; however, it contains interesting qualitative information. This 3D reconstruction exhibits edge enhancement and contrast enhancement for nanostructures compared with the conventional 3D refractive index reconstruction and thus could be used to localize nanoparticles such as lipids inside a biological sample.
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9
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Cheng S, Fu S, Kim YM, Song W, Li Y, Xue Y, Yi J, Tian L. Single-cell cytometry via multiplexed fluorescence prediction by label-free reflectance microscopy. SCIENCE ADVANCES 2021; 7:eabe0431. [PMID: 33523908 PMCID: PMC7810377 DOI: 10.1126/sciadv.abe0431] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Accepted: 11/19/2020] [Indexed: 05/08/2023]
Abstract
Traditional imaging cytometry uses fluorescence markers to identify specific structures but is limited in throughput by the labeling process. We develop a label-free technique that alleviates the physical staining and provides multiplexed readouts via a deep learning-augmented digital labeling method. We leverage the rich structural information and superior sensitivity in reflectance microscopy and show that digital labeling predicts accurate subcellular features after training on immunofluorescence images. We demonstrate up to three times improvement in the prediction accuracy over the state of the art. Beyond fluorescence prediction, we demonstrate that single cell-level structural phenotypes of cell cycles are correctly reproduced by the digital multiplexed images, including Golgi twins, Golgi haze during mitosis, and DNA synthesis. We further show that the multiplexed readouts enable accurate multiparametric single-cell profiling across a large cell population. Our method can markedly improve the throughput for imaging cytometry toward applications for phenotyping, pathology, and high-content screening.
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Affiliation(s)
- Shiyi Cheng
- Department of Electrical and Computer Engineering, Boston University, Boston, MA 02215, USA
| | - Sipei Fu
- Department of Biology, Boston University, Boston, MA 02215, USA
| | - Yumi Mun Kim
- Department of Philosophy & Neuroscience, Boston University, Boston, MA 02215, USA
| | - Weiye Song
- Department of Medicine, Boston University School of Medicine, Boston Medical Center, Boston, MA 02118, USA
| | - Yunzhe Li
- Department of Electrical and Computer Engineering, Boston University, Boston, MA 02215, USA
| | - Yujia Xue
- Department of Electrical and Computer Engineering, Boston University, Boston, MA 02215, USA
| | - Ji Yi
- Department of Electrical and Computer Engineering, Boston University, Boston, MA 02215, USA.
- Department of Medicine, Boston University School of Medicine, Boston Medical Center, Boston, MA 02118, USA
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Lei Tian
- Department of Electrical and Computer Engineering, Boston University, Boston, MA 02215, USA.
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10
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Yurdakul C, Ünlü MS. Computational nanosensing from defocus in single particle interferometric reflectance microscopy. OPTICS LETTERS 2020; 45:6546-6549. [PMID: 33258864 DOI: 10.1364/ol.409458] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Accepted: 10/25/2020] [Indexed: 06/12/2023]
Abstract
Single particle interferometric reflectance (SPIR) microscopy has been studied as a powerful imaging platform for label-free and highly sensitive biological nanoparticle detection and characterization. SPIR's interferometric nature yields a unique 3D defocus intensity profile of the nanoparticles over a large field of view. Here, we utilize this defocus information to recover high signal-to-noise ratio nanoparticle images with a computationally and memory efficient reconstruction framework. Our direct inversion approach recovers this image from a 3D defocus intensity stack using the vectorial-optics-based forward model developed for sub-diffraction-limited dielectric nanoparticles captured on a layered substrate. We demonstrate proof-of-concept experiments on silica beads with a 50 nm nominal diameter.
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11
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Song W, Matlock A, Fu S, Qin X, Feng H, Gabel CV, Tian L, YI J. LED array reflectance microscopy for scattering-based multi-contrast imaging. OPTICS LETTERS 2020; 45:1647-1650. [PMID: 32235964 PMCID: PMC7278208 DOI: 10.1364/ol.387434] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Accepted: 02/01/2020] [Indexed: 05/24/2023]
Abstract
LED array microscopy is an emerging platform for computational imaging with significant utility for biological imaging. Existing LED array systems often exploit transmission imaging geometries of standard brightfield microscopes that leave the rich backscattered field undetected. This backscattered signal contains high-resolution sample information with superb sensitivity to subtle structural features that make it ideal for biological sensing and detection. Here, we develop an LED array reflectance microscope capturing the sample's backscattered signal. In particular, we demonstrate multimodal brightfield, darkfield, and differential phase contrast imaging on fixed and living biological specimens including Caenorhabditis elegans (C. elegans), zebrafish embryos, and live cell cultures. Video-rate multimodal imaging at 20 Hz records real time features of freely moving C. elegans and the fast beating heart of zebrafish embryos. Our new reflectance mode is a valuable addition to the LED array microscopic toolbox.
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Affiliation(s)
- Weiye Song
- Department of Medicine, Boston University School of Medicine, Boston Medical Center, Boston, Massachusetts 02118, USA
| | - Alex Matlock
- Department of Electrical and Computer Engineering, Boston University, Boston, Massachusetts 02215, USA
| | - Sipei Fu
- Department of Medicine, Boston University School of Medicine, Boston Medical Center, Boston, Massachusetts 02118, USA
| | - Xiaodan Qin
- Departments of Pharmacology and Medicine, Section of Hematology and Medical Oncology, Cancer Research Center, Boston University School of Medicine, Boston, Massachusetts 02118, USA
| | - Hui Feng
- Departments of Pharmacology and Medicine, Section of Hematology and Medical Oncology, Cancer Research Center, Boston University School of Medicine, Boston, Massachusetts 02118, USA
| | - Christopher V. Gabel
- Department of Physiology and Biophysics, Boston University School of Medicine, Boston, Massachusetts 02118, USA
| | - Lei Tian
- Department of Electrical and Computer Engineering, Boston University, Boston, Massachusetts 02215, USA
| | - Ji YI
- Department of Medicine, Boston University School of Medicine, Boston Medical Center, Boston, Massachusetts 02118, USA
- Department of Electrical and Computer Engineering, Boston University, Boston, Massachusetts 02215, USA
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, USA
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