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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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Lopes TS, Alves GG, Pereira MR, Granjeiro JM, Leite PEC. Advances and potential application of gold nanoparticles in nanomedicine. J Cell Biochem 2019; 120:16370-16378. [DOI: 10.1002/jcb.29044] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Revised: 05/03/2019] [Accepted: 05/07/2019] [Indexed: 12/13/2022]
Affiliation(s)
- Talíria Silva Lopes
- Graduate Program in Sciences and Biotechnology, Fluminense Federal University – UFF Niteroi RJ Brazil
| | - Gutemberg Gomes Alves
- Cell and Molecular Biology Department Biology Institute, Fluminense Federal University – UFF Niteroi RJ Brazil
| | | | - Jose Mauro Granjeiro
- Dental School – Fluminense Federal University – UFF Niteroi RJ Brazil
- Laboratory of Bioengineering and in Vitro Toxicology Directory of Metrology Applied to Life Sciences – Dimav, National Institute of Metrology Quality and Technology – INMETRO Duque de Caxias RJ Brazil
| | - Paulo Emílio Corrêa Leite
- Laboratory of Bioengineering and in Vitro Toxicology Directory of Metrology Applied to Life Sciences – Dimav, National Institute of Metrology Quality and Technology – INMETRO Duque de Caxias RJ Brazil
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Majeed H, Sridharan S, Mir M, Ma L, Min E, Jung W, Popescu G. Quantitative phase imaging for medical diagnosis. JOURNAL OF BIOPHOTONICS 2017; 10:177-205. [PMID: 27539534 DOI: 10.1002/jbio.201600113] [Citation(s) in RCA: 65] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2016] [Revised: 07/06/2016] [Accepted: 07/13/2016] [Indexed: 05/19/2023]
Abstract
Optical microscopy is an indispensable diagnostic tool in modern healthcare. As a prime example, pathologists rely exclusively on light microscopy to investigate tissue morphology in order to make a diagnosis. While advances in light microscopy and contrast markers allow pathologists to visualize cells and tissues in unprecedented detail, the interpretation of these images remains largely subjective, leading to inter- and intra-observer discrepancy. Furthermore, conventional microscopy images capture qualitative information which makes it difficult to automate the process, reducing the throughput achievable in the diagnostic workflow. Quantitative Phase Imaging (QPI) techniques have been advanced in recent years to address these two challenges. By quantifying physical parameters of cells and tissues, these systems remove subjectivity from the disease diagnosis process and allow for easier automation to increase throughput. In addition to providing quantitative information, QPI systems are also label-free and can be easily assimilated into the current diagnostic workflow in the clinic. In this paper we review the advances made in disease diagnosis by QPI techniques. We focus on the areas of hematological diagnosis and cancer pathology, which are the areas where most significant advances have been made to date. [Image adapted from Y. Park, M. Diez-Silva, G. Popescu, G. Lykotrafitis, W. Choi, M. S. Feld, and S. Suresh, Proc. Natl. Acad. Sci. 105, 13730-13735 (2008).].
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Affiliation(s)
- Hassaan Majeed
- Quantitative Light Imaging Lab, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana Champaign, 405 N. Mathews Ave., Urbana, IL, 61801, USA
| | - Shamira Sridharan
- Biomedical Engineering Department, University of California Davis, Genome and Biomedical Sciences Facility #2603B, 451 Health Science Dr., Davis, CA, 95616, USA
| | - Mustafa Mir
- Molecular and Cell Biology, University of California, Berkeley, 485 Li Ka Shing Center, 94720, Berkeley, CA, USA
| | - Lihong Ma
- Institute of Information Optics, Zhejiang Normal University, Jinhua, 321004, China
| | - Eunjung Min
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, 50 UNIST-gil, Ulsan, 44919, Republic of Korea
| | - Woonggyu Jung
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, 50 UNIST-gil, Ulsan, 44919, Republic of Korea
- Center for Soft and Living Matter, Institute for Basic Science (IBS), 50 UNIST-gil, Ulsan, 44919, Republic of Korea
| | - Gabriel Popescu
- Quantitative Light Imaging Lab, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana Champaign, 405 N. Mathews Ave., Urbana, IL, 61801, USA
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Krafft C. Modern trends in biophotonics for clinical diagnosis and therapy to solve unmet clinical needs. JOURNAL OF BIOPHOTONICS 2016; 9:1362-1375. [PMID: 27943650 DOI: 10.1002/jbio.201600290] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2016] [Accepted: 11/16/2016] [Indexed: 06/06/2023]
Abstract
This contribution covers recent original research papers in the biophotonics field. The content is organized into main techniques such as multiphoton microscopy, Raman spectroscopy, infrared spectroscopy, optical coherence tomography and photoacoustic tomography, and their applications in the context of fluid, cell, tissue and skin diagnostics. Special attention is paid to vascular and blood flow diagnostics, photothermal and photodynamic therapy, tissue therapy, cell characterization, and biosensors for biomarker detection.
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Affiliation(s)
- Christoph Krafft
- Leibniz Institute of Photonic Technology, Albert-Einstein-Str. 9, 07745, Jena, Germany
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Belashov AV, Zhikhoreva AA, Belyaeva TN, Kornilova ES, Petrov NV, Salova AV, Semenova IV, Vasyutinskii OS. Digital holographic microscopy in label-free analysis of cultured cells' response to photodynamic treatment. OPTICS LETTERS 2016; 41:5035-5038. [PMID: 27805679 DOI: 10.1364/ol.41.005035] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
A methodology providing noninvasive monitoring and evaluation of the effect of photodynamic treatment on live cells in vitro is presented. Variations in morphological characteristics of cells in the course and after treatment are recorded by means of digital holographic microscopy. High-precision measurements of phase shift gained by probe radiation in HeLa and human endometrial mesenchymal stem cell cultures demonstrate for the first time changes of their volume occurred in response to treatment.
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