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Quantitative phase imaging in biomedicine

Abstract

Quantitative phase imaging (QPI) has emerged as a valuable method for investigating cells and tissues. QPI operates on unlabelled specimens and, as such, is complementary to established fluorescence microscopy, exhibiting lower phototoxicity and no photobleaching. As the images represent quantitative maps of optical path length delays introduced by the specimen, QPI provides an objective measure of morphology and dynamics, free of variability due to contrast agents. Owing to the tremendous progress witnessed especially in the past 10–15 years, a number of technologies have become sufficiently reliable and translated to biomedical laboratories. Commercialization efforts are under way and, as a result, the QPI field is now transitioning from a technology-development-driven to an application-focused field. In this Review, we aim to provide a critical and objective overview of this dynamic research field by presenting the scientific context, main principles of operation and current biomedical applications.

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Fig. 1: Principles of QPI measurements.
Fig. 2: Converting QPI into light-scattering information.
Fig. 3: Approaches for tomographic QPI.
Fig. 4: Applications of QPI in basic science.
Fig. 5: Applications of QPI in medicine.

References

  1. Evanko, D., Heinrichs, A. & Rosenthal, C. Milestones in light microscopy. Nat. Cell Biol. S5–S20 (2009).

  2. Popescu, G. Quantitative Phase Imaging of Cells and Tissues (McGraw-Hill, New York, 2011).

  3. Abbe, E. Beiträge zur Theorie des Mikroskops und der mikroskopischen Wahrnehmung. Arch. Mikrosk. Anat. 9, 413–418 (1873)..

    Google Scholar 

  4. Hell, S. W. & Wichmann, J. Breaking the diffraction resolution limit by stimulated emission: stimulated-emission-depletion fluorescence microscopy. Opt. Lett. 19, 780–782 (1994).

    ADS  Google Scholar 

  5. Tuchin, V. V. & Society of Photo-optical Instrumentation Engineers. Tissue Optics: Light Scattering Methods and Instruments For Medical Diagnosis 2nd edn (SPIE/International Society for Optical Engineering, Bellingham, 2007).

  6. Diaspro, A. Optical Fluorescence Microscopy (Springer, Berlin, 2011).

  7. Kumar, V., Abbas, A. K., Fausto, N. & Aster, J. C. Robbins and Cotran Pathologic Basis of Disease (Elsevier Health Sciences, Oxford, 2014).

  8. Zernike, F. How I discovered phase contrast. Science 121, 345–349 (1955).

    ADS  Google Scholar 

  9. Born, M. & Wolf, E. Principles of Optics: Electromagnetic Theory of Propagation, Interference and Diffraction of Light 7th edn (Cambridge Univ. Press, 1999).

  10. Gabor, D. A new microscopic principle. Nature 161, 777–778 (1948).

    ADS  Google Scholar 

  11. Lohmann, A. Optische Einseitenbandübertragung angewandt auf das Gabor-Mikroskop. Opt. Acta 3, 97–99 (1956)..

    Google Scholar 

  12. Leith, E. N. & Upatnieks, J. Reconstructed wavefronts and communication theory. J. Opt. Soc. Am. 52, 1123–1130 (1962).

    ADS  Google Scholar 

  13. Poon, T.-C. Digital Holography and Three-dimensional Display: Principles and Applications (Springer Science & Business Media, New York, 2006).

  14. Boas, D. A., Pitris, C. & Ramanujam, N. (eds) Handbook of Biomedical Optics (CRC Press, Boca Raton, 2016).

  15. Cuche, E., Bevilacqua, F. & Depeursinge, C. Digital holography for quantitative phase-contrast imaging. Opt. Lett. 24, 291–293 (1999).

    ADS  Google Scholar 

  16. Creath, K. Phase-measurement interferometry techniques. Prog. Opt. 26, 349–393 (1988).

    ADS  Google Scholar 

  17. Huang, D. et al. Optical coherence tomography. Science 254, 1178–1181 (1991).

    ADS  Google Scholar 

  18. deBoer, J. F., Milner, T. E., vanGemert, M. J. C. & Nelson, J. S. Two-dimensional birefringence imaging in biological tissue by polarization-sensitive optical coherence tomography. Opt. Lett. 22, 934–936 (1997).

    ADS  Google Scholar 

  19. Izatt, J. A., Kulkami, M. D., Yazdanfar, S., Barton, J. K. & Welch, A. J. In vivo bidirectional color Doppler flow imaging of picoliter blood volumes using optical coherence tomograghy. Opt. Lett. 22, 1439–1441 (1997).

    ADS  Google Scholar 

  20. Hitzenberger, C. K. & Fercher, A. F. Differential phase contrast in optical coherence tomography. Opt. Lett. 24, 622–624 (1999).

    ADS  Google Scholar 

  21. Yang, C. H. et al. Interferometric phase-dispersion microscopy. Opt. Lett. 25, 1526–1528 (2000).

    ADS  Google Scholar 

  22. Yang, C. et al. Phase-referenced interferometer with subwavelength and subhertz sensitivity applied to the study of cell membrane dynamics. Opt. Lett. 26, 1271–1273 (2001).

    ADS  Google Scholar 

  23. Choma, M. A., Ellerbee, A. K., Yang, C. H., Creazzo, T. L. & Izatt, J. A. Spectral-domain phase microscopy. Opt. Lett. 30, 1162–1164 (2005).

    ADS  Google Scholar 

  24. Joo, C., Akkin, T., Cense, B., Park, B. H. & de Boer, J. E. Spectral-domain optical coherence phase microscopy for quantitative phase-contrast imaging. Opt. Lett. 30, 2131–2133 (2005).

    ADS  Google Scholar 

  25. Paganin, D. & Nugent, K. A. Noninterferometric phase imaging with partially coherent light. Phys. Rev. Lett. 80, 2586–2589 (1998).

    ADS  Google Scholar 

  26. Takeda, M., Ina, H. & Kobayashi, S. Fourier-transform method of fringe-pattern analysis for computer-based topography and interferometry. J. Opt. Soc. Am. 72, 156–160 (1982).

    ADS  Google Scholar 

  27. Liebling, M., Blu, T. & Unser, M. Complex-wave retrieval from a single off-axis hologram. J. Opt. Soc. Am. A 21, 367–377 (2004).

    ADS  Google Scholar 

  28. Michelson, A. A. & Morley, E. W. On the relative motion of the luminiferous ether. Am. J. Sci. 34, 333–345 (1887).

    ADS  MATH  Google Scholar 

  29. Hosseini, P. et al. Pushing phase and amplitude sensitivity limits in interferometric microscopy. Opt. Lett. 41, 1656–1659 (2016).

    ADS  Google Scholar 

  30. A triumph of sensitivity. Nat. Photon. 11, 677 (2017).

  31. Popescu, G., Ikeda, T., Dasari, R. R. & Feld, M. S. Diffraction phase microscopy for quantifying cell structure and dynamics. Opt. Lett. 31, 775–777 (2006).

    ADS  Google Scholar 

  32. Kim, T. et al. White-light diffraction tomography of unlabelled live cells. Nat. Photon. 8, 256–263 (2014).

    ADS  Google Scholar 

  33. Nguyen, T. H., Kandel, M. E., Rubessa, M., Wheeler, M. B. & Popescu, G. Gradient light interference microscopy for 3D imaging of unlabeled specimens. Nat. Commun. 8, 210 (2017).

    ADS  Google Scholar 

  34. Stockton, P. A., Field, J. J. & Bartels, R. A. Single pixel quantitative phase imaging with spatial frequency projections. Methods 136, 24–34 (2018).

    Google Scholar 

  35. Yin, Z. Z., Kanade, T. & Chen, M. Understanding the phase contrast optics to restore artifact-free microscopy images for segmentation. Med. Image Anal. 16, 1047–1062 (2012).

    Google Scholar 

  36. Dubois, F., Requena, M.-L. N., Minetti, C., Monnom, O. & Istasse, E. Partial spatial coherence effects in digital holographic microscopy with a laser source. Appl. Opt. 43, 1131–1139 (2004).

    ADS  Google Scholar 

  37. Mico, V., Zalevsky, Z. & García, J. Common-path phase-shifting digital holographic microscopy: a way to quantitative phase imaging and superresolution. Opt. Commun. 281, 4273–4281 (2008).

    ADS  Google Scholar 

  38. Greenbaum, A. et al. Imaging without lenses: achievements and remaining challenges of wide-field on-chip microscopy. Nat. Methods 9, 889–895 (2012).

    Google Scholar 

  39. Rubin, M., Dardikman, G., Mirsky, S. K., Turko, N. A. & Shaked, N. T. Six-pack off-axis holography. Opt. Lett. 42, 4611–4614 (2017).

    ADS  Google Scholar 

  40. Chen, S., Li, C. & Zhu, Y. Sensitivity evaluation of quantitative phase imaging: a study of wavelength shifting interferometry. Opt. Lett. 42, 1088–1091 (2017).

    ADS  Google Scholar 

  41. Sinha, A., Lee, J., Li, S. & Barbastathis, G. Lensless computational imaging through deep learning. Optica 4, 1117–1125 (2017).

    Google Scholar 

  42. Rivenson, Y., Zhang, Y., Günaydin, H., Teng, D. & Ozcan, A. Phase recovery and holographic image reconstruction using deep learning in neural networks. Light Sci. Appl. 7, 17141 (2018).

    Google Scholar 

  43. Wu, Y. et al. Extended depth-of-field in holographic image reconstruction using deep learning based auto-focusing and phase-recovery. Optica 5, 704–710 (2018).

    Google Scholar 

  44. Bohren, C. F. & Huffman, D. R. Absorption and Scattering of Light by Small Particles (Wiley, New York, 1983).

  45. Ding, H. F., Wang, Z., Nguyen, F., Boppart, S. A. & Popescu, G. Fourier transform light scattering of inhomogeneous and dynamic structures. Phys. Rev. Lett. 101, 238102 (2008).

    ADS  Google Scholar 

  46. Berne, B. J. & Pecora, R. Dynamic Light Scattering with Applications to Chemistry, Biology and Physics (Wiley, New York, 1976).

  47. Wang, R. et al. Dispersion-relation phase spectroscopy of intracellular transport. Opt. Express 19, 20571–20579 (2011).

    ADS  Google Scholar 

  48. Wolf, E. Three-dimensional structure determination of semi-transparent objects from holographic data. Opt. Commun. 1, 153–156 (1969).

    ADS  Google Scholar 

  49. Fercher, A., Bartelt, H., Becker, H. & Wiltschko, E. Image formation by inversion of scattered field data: experiments and computational simulation. Appl. Opt. 18, 2427–2439 (1979).

    ADS  Google Scholar 

  50. Lauer, V. New approach to optical diffraction tomography yielding a vector equation of diffraction tomography and a novel tomographic microscope. J. Microsc. 205, 165–176 (2002).

    MathSciNet  Google Scholar 

  51. Choi, W. et al. Tomographic phase microscopy. Nat. Methods 4, 717–719 (2007).

    Google Scholar 

  52. Cotte, Y. et al. Marker-free phase nanoscopy. Nat. Photon. 7, 113–117 (2013).

    ADS  Google Scholar 

  53. Barty, A., Nugent, K. A., Roberts, A. & Paganin, D. Quantitative phase tomography. Opt. Commun. 175, 329–336 (2000).

    ADS  Google Scholar 

  54. Charrière, F. et al. Cell refractive index tomography by digital holographic microscopy. Opt. Lett. 31, 178–180 (2006).

    ADS  Google Scholar 

  55. Kuś, A., Dudek, M., Kemper, B., Kujawińska, M. & Vollmer, A. Tomographic phase microscopy of living three-dimensional cell cultures. J. Biomed. Opt. 19, 046009 (2014).

    ADS  Google Scholar 

  56. Habaza, M., Gilboa, B., Roichman, Y. & Shaked, N. T. Tomographic phase microscopy with 180 degrees rotation of live cells in suspension by holographic optical tweezers. Opt. Lett. 40, 1881–1884 (2015).

    ADS  Google Scholar 

  57. Merola, F. et al. Tomographic flow cytometry by digital holography. Light Sci. Appl. 6, e16241 (2017).

    Google Scholar 

  58. Horstmeyer, R., Chung, J., Ou, X., Zheng, G. & Yang, C. Diffraction tomography with Fourier ptychography. Optica 3, 827–835 (2016).

    Google Scholar 

  59. Kim, M.-K. Tomographic three-dimensional imaging of a biological specimen using wavelength-scanning digital interference holography. Opt. Express 7, 305–310 (2000).

    ADS  Google Scholar 

  60. Pan, Y., Lankenou, E., Welzel, J., Birngruber, R. & Engelhardt, R. Optical coherence-gated imaging of biological tissues. IEEE J. Sel. Top. Quantum Electron. 2, 1029–1034 (1996).

    ADS  Google Scholar 

  61. Schmitt, J. M. Optical coherence tomography (OCT): a review. IEEE J. Sel. Top. Quantum Electron. 5, 1205–1215 (1999).

    ADS  Google Scholar 

  62. Bao, C., Barbastathis, G., Ji, H., Shen, Z. & Zhang, Z. Coherence retrieval using trace regularization. SIAM J. Imaging Sci. 11, 679–706 (2018).

    MathSciNet  Google Scholar 

  63. Kamilov, U. S. et al. Learning approach to optical tomography. Optica 2, 517–522 (2015).

    Google Scholar 

  64. Cotte, Y. et al. Realistic 3D coherent transfer function inverse filtering of complex fields. Biomed. Opt. Express 2, 2216–2230 (2011).

    Google Scholar 

  65. Jourdain, P. et al. Determination of transmembrane water fluxes in neurons elicited by glutamate ionotropic receptors and by the cotransporters KCC2 and NKCC1: a digital holographic microscopy study. J. Neurosci. 31, 11846–11854 (2011).

    Google Scholar 

  66. Jourdain, P. et al. Simultaneous optical recording in multiple cells by digital holographic microscopy of chloride current associated to activation of the ligand-gated chloride channel GABAA receptor. PLoS ONE 7, e51041 (2012).

    ADS  Google Scholar 

  67. Marquet, P., Depeursinge, C. & Magistretti, P. J. Review of quantitative phase-digital holographic microscopy: promising novel imaging technique to resolve neuronal network activity and identify cellular biomarkers of psychiatric disorders. Neurophotonics 1, 020901 (2014).

    Google Scholar 

  68. Weitzman, J. B. Growing without a size checkpoint. J. Biol. 2, 3 (2003).

    Google Scholar 

  69. Godin, M. et al. Using buoyant mass to measure the growth of single cells. Nat. Methods 7, 387–390 (2010).

    Google Scholar 

  70. Mitchison, J. M. Single cell studies of the cell cycle and some models. Theor. Biol. Med. Model. 2, 4 (2005).

    Google Scholar 

  71. Popescu, G. et al. Optical imaging of cell mass and growth dynamics. Am. J. Physiol. Cell Physiol. 295, C538–C544 (2008).

    Google Scholar 

  72. Mitchison, J. M. Growth during the cell cycle. Int. Rev. Cytol. 226, 165–258 (2003).

    Google Scholar 

  73. Tzur, A., Kafri, R., LeBleu, V. S., Lahav, G. & Kirschner, M. W. Cell growth and size homeostasis in proliferating animal cells. Science 325, 167–171 (2009).

    ADS  Google Scholar 

  74. Davies, H. G. & Wilkins, M. H. F. Interference microscopy and mass determination. Nature 161, 541 (1952).

    ADS  Google Scholar 

  75. Barer, R. Interference microscopy and mass determination. Nature 169, 366–367 (1952).

    ADS  Google Scholar 

  76. Zicha, D. & Dunn, G. A. An image-processing system for cell behavior studies in subconfluent cultures. J. Microsc. 179, 11–21 (1995).

    Google Scholar 

  77. Zhao, H., Brown, P. H. & Schuck, P. On the distribution of protein refractive index increments. Biophys. J. 100, 2309–2317 (2011).

    ADS  Google Scholar 

  78. Mir, M. et al. Optical measurement of cycle-dependent cell growth. Proc. Natl Acad. Sci. USA 108, 13124–13129 (2011).

    ADS  Google Scholar 

  79. Sung, Y., Choi, W., Lue, N., Dasari, R. R. & Yaqoob, Z. Stain-free quantification of chromosomes in live cells using regularized tomographic phase microscopy. PLoS ONE 7, e49502 (2012).

    ADS  Google Scholar 

  80. Shribak, M., Larkin, K. G. & Biggs, D. Mapping optical path length and image enhancement using quantitative orientation-independent differential interference contrast microscopy. J. Biomed. Opt. 22, 016006 (2017).

    ADS  Google Scholar 

  81. Bedrossian, M., Lindensmith, C. & Nadeau, J. L. Digital holographic microscopy, a method for detection of microorganisms in plume samples from Enceladus and other icy worlds. Astrobiology 17, 913–925 (2017).

    ADS  Google Scholar 

  82. Yourassowsky, C. & Dubois, F. High throughput holographic imaging-in-flow for the analysis of a wide plankton size range. Opt. Express 22, 6661–6673 (2014).

    ADS  Google Scholar 

  83. Bon, P. et al. Three-dimensional nanometre localization of nanoparticles to enhance super-resolution microscopy. Nat. Commun. 6, 7764 (2015).

    Google Scholar 

  84. Bon, P., Aknoun, S., Monneret, S. & Wattellier, B. Enhanced 3D spatial resolution in quantitative phase microscopy using spatially incoherent illumination. Opt. Express 22, 8654–8671 (2014).

    ADS  Google Scholar 

  85. Mudanyali, O. et al. Wide-field optical detection of nanoparticles using on-chip microscopy and self-assembled nanolenses. Nat. Photon. 7, 247–254 (2013).

    ADS  Google Scholar 

  86. Yu, X. et al. Measurement of the traction force of biological cells by digital holography. Biomed. Opt. Express 3, 153–159 (2012).

    Google Scholar 

  87. Kemper, B. et al. Investigation of living pancreas tumor cells by digital holographic microscopy. J. Biomed. Opt. 11, 034005–034008 (2006).

    ADS  Google Scholar 

  88. Simon, B., Debailleul, M., Beghin, A., Tourneur, Y. & Haeberle, O. High-resolution tomographic diffractive microscopy of biological samples. J. Biophoton. 3, 462–467 (2010).

    Google Scholar 

  89. Hsu, W.-C., Su, J.-W., Chang, C.-C. & Sung, K.-B. Investigating the backscattering characteristics ofindividual normal and cancerous cells based on experimentally determined three-dimensional refractive index distributions. Proc. SPIE 8553, 85531O (2012).

    Google Scholar 

  90. Shaked, N. T., Satterwhite, L. L., Truskey, G. A., Wax, A. P. & Telen, M. J. Quantitative microscopy and nanoscopy of sickle red blood cells performed by wide field digital interferometry. J. Biomed. Opt. 16, 030506 (2011).

    ADS  Google Scholar 

  91. Lee, S. et al. Refractive index tomograms and dynamic membrane fluctuations of red blood cells from patients with diabetes mellitus. Sci. Rep. 7, 1039 (2017).

    ADS  Google Scholar 

  92. Khan, S., Jesacher, A., Nussbaumer, W., Bernet, S. & Ritsch‐Marte, M. Quantitative analysis of shape and volume changes in activated thrombocytes in real time by single‐shot spatial light modulator‐based differential interference contrast imaging. J. Biophoton. 4, 600–609 (2011).

    Google Scholar 

  93. Haifler, M. et al. Interferometric phase microscopy for label-free morphological evaluation of sperm cells. Fertil. Steril. 104, 43–47.e42 (2015).

    Google Scholar 

  94. Lenz, P. et al. Digital holographic microscopy quantifies the degree of inflammation in experimental colitis. Integr. Biol. 5, 624–630 (2013).

    Google Scholar 

  95. Bettenworth, D. et al. Quantitative stain-free and continuous multimodal monitoring of wound healing in vitro with digital holographic microscopy. PLoS ONE 9, e107317 (2014).

    ADS  Google Scholar 

  96. Kwon, S. et al. Mitochondria-targeting indolizino [3,2-c] quinolines as novel class of photosensitizers for photodynamic anticancer activity. Eur. J. Med. Chem. 148, 116–127 (2018).

    Google Scholar 

  97. Madabhushi, A. & Lee, G. Image analysis and machine learning in digital pathology: challenges and opportunities. Med. Image Anal. 33, 170–175 (2016).

    Google Scholar 

  98. Yoon, J. et al. Identification of non-activated lymphocytes using three-dimensional refractive index tomography and machine learning. Sci. Rep. 7, 6654 (2017).

    ADS  Google Scholar 

  99. Jo, Y. et al. Holographic deep learning for rapid optical screening of anthrax spores. Sci. Adv. 3, e1700606 (2017).

    ADS  Google Scholar 

  100. Hejna, M., Jorapur, A., Song, J. S. & Judson, R. L. High accuracy label-free classification of single-cell kinetic states from holographic cytometry of human melanoma cells. Sci. Rep. 7, 11943 (2017).

    ADS  Google Scholar 

  101. Holmström, O. et al. Point-of-care mobile digital microscopy and deep learning for the detection of soil-transmitted helminths and Schistosoma haematobium. Global Health Action 10, 1337325 (2017).

    Google Scholar 

  102. Huang, B., Bates, M. & Zhuang, X. Super resolution fluorescence microscopy. Annu. Rev. Biochem. 78, 993–1016 (2009).

    Google Scholar 

  103. Alexandrov, S., Hillman, T., Gutzler, T. & Sampson, D. Synthetic aperture Fourier holographic optical microscopy. Phys. Rev. Lett. 97, 168102 (2006).

    ADS  Google Scholar 

  104. Pavillon, N., Hobro, A. J., Akira, S. & Smith, N. I. Noninvasive detection of macrophage activation with single-cell resolution through machine learning. Proc. Natl Acad. Sci. USA https://doi.org/10.1073/pnas.1711872115 (2018).

    Google Scholar 

  105. Dunn, G. A. & Zicha, D. Dynamics of fibroblast spreading. J. Cell Sci. 108, 1239–1249 (1995).

    Google Scholar 

  106. Greenbaum, A. et al. Wide-field computational imaging of pathology slides using lens-free on-chip microscopy.Sci. Transl. Med. 6, 267ra175 (2014).

    Google Scholar 

  107. Popescu, G. et al. Fourier phase microscopy for investigation of biological structures and dynamics. Opt. Lett. 29, 2503–2505 (2004).

    ADS  Google Scholar 

  108. Popescu, G., Badizadegan, K., Dasari, R. R. & Feld, M. S. Observation of dynamic subdomains in red blood cells. J. Biomed. Opt. Lett. 11, 040503 (2006).

    ADS  Google Scholar 

  109. Ikeda, T., Popescu, G., Dasari, R. R. & Feld, M. S. Hilbert phase microscopy for investigating fast dynamics in transparent systems. Opt. Lett. 30, 1165–1168 (2005).

    ADS  Google Scholar 

  110. Popescu, G. et al. Erythrocyte structure and dynamics quantified by Hilbert phase microscopy. J. Biomed. Opt. Lett. 10, 060503 (2005).

    ADS  Google Scholar 

  111. Lue, N. et al. Tissue refractometry using Hilbert phase microscopy. Opt. Lett. 32, 3522–3524 (2007).

    ADS  Google Scholar 

  112. Marquet, P. et al. Digital holographic microscopy: a noninvasive contrast imaging technique allowing quantitative visualization of living cells with subwavelength axial accuracy. Opt. Lett. 30, 468–470 (2005).

    ADS  Google Scholar 

  113. Uttam, S. et al. Early prediction of cancer progression by depth-resolved nanoscale mapping of nuclear architecture from unstained tissue specimens. Cancer Res. 75, 4718–4727 (2015).

    Google Scholar 

  114. Park, Y. K. et al. Refractive index maps and membrane dynamics of human red blood cells parasitized by Plasmodium falciparum. Proc. Natl Acad. Sci. USA 105, 13730–13735 (2008).

    ADS  Google Scholar 

  115. Hosseini, P. et al. Cellular normoxic biophysical markers of hydroxyurea treatment in sickle cell disease. Proc. Natl Acad. Sci. USA 113, 9527–9532 (2016).

    ADS  Google Scholar 

  116. Bon, P., Maucort, G., Wattellier, B. & Monneret, S. Quadriwave lateral shearing interferometry for quantitative phase microscopy of living cells. Opt. Express 17, 13080–13094 (2009).

    ADS  Google Scholar 

  117. Mitchell, S., Roy, K., Zangle, T. A. & Hoffmann, A. Nongenetic origins of cell-to-cell variability in B lymphocyte proliferation. Proc. Natl Acad. Sci. USA 115, E2888–E2897 (2018).

    Google Scholar 

  118. Kolman, P. & Chmelík, R. Coherence-controlled holographic microscope. Opt. Express 18, 21990–22004 (2010).

    ADS  Google Scholar 

  119. Štrbková, L. et al. The adhesion of normal human dermal fibroblasts to the cyclopropylamine plasma polymers studied by holographic microscopy. Surf. Coat. Technol. 295, 70–77 (2016).

    Google Scholar 

  120. Wang, Z. et al. Spatial light interference microscopy (SLIM). Opt. Express 19, 1016–1026 (2011).

    ADS  Google Scholar 

  121. Mir, M. et al. Label-free characterization of emerging human neuronal networks. Sci. Rep. 4, 04434 (2014).

    Google Scholar 

  122. Majeed, H., Nguyen, T. H., Kandel, M. E., Kajdacsy-Balla, A. & Popescu, G. Label-free quantitative evaluation of breast tissue using spatial light interference microscopy (SLIM). Sci. Rep. 8, 6875 (2018).

    ADS  Google Scholar 

  123. Majeed, H. et al. Magnified image spatial spectrum (MISS) microscopy for nanometer and millisecond scale label-free imaging. Opt. Express 26, 5423–5440 (2018).

    ADS  Google Scholar 

  124. Kim, K. et al. Optical diffraction tomography techniques for the study of cell pathophysiology. J. Biomed. Photon. Eng. 2, 2 (2016).

    Google Scholar 

  125. Kim, K. et al. Three dimensional label-free imaging and quantification of lipid droplets in live hepatocytes. Sci. Rep. 6, 36815 (2016).

    ADS  Google Scholar 

  126. Kim, K. et al. High-resolution three-dimensional imaging of red blood cells parasitized by Plasmodium falciparum and in situ hemozoin crystals using optical diffraction tomography. J. Biomed. Opt. 19, 011005 (2013).

    Google Scholar 

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Acknowledgements

Y.K.P. was supported by the National Research Foundation of Korea (2017M3C1A3013923, 2015R1A3A2066550, 2017K000396). G.P. was supported by the National Science Foundation (STC CBET 0939511, NSF BRAIN EAGER DBI 1450962, IIP-1353368).

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Correspondence to Gabriel Popescu.

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Y.K.P. has financial interest in Tomocube. C.D. has financial interest in Lyncee Tech and Nanolive. G.P. has financial interest in Phi Optics. All these companies commercialize QPI instruments.

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Park, Y., Depeursinge, C. & Popescu, G. Quantitative phase imaging in biomedicine. Nature Photon 12, 578–589 (2018). https://doi.org/10.1038/s41566-018-0253-x

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