Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Label-free biomedical optical imaging

Abstract

Label-free optical imaging employs natural and non-destructive approaches to visualize biomedical samples for both biological assays and clinical diagnosis. At present, this field revolves around multiple technology-oriented communities, each with a specific focus on a particular modality, despite the existence of shared challenges and applications. As a result, biologists or clinical researchers who require label-free imaging are often not aware of the most appropriate modality to use. This Review presents a comprehensive overview of, and comparison among, different label-free imaging modalities and discusses common challenges and applications. We expect this Review to facilitate collaborative interactions between imaging communities, push the field forwards and foster technological advancements and biophysical discoveries, as well as facilitate new avenues in clinical detection, diagnosis and monitoring of diseases.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Comparison of imaging methods of human sperm cells.
Fig. 2: Label-free OCT applications.
Fig. 3: Image atlas obtained by SLAM.
Fig. 4: Single-shot label-free multimodal nonlinear imaging.
Fig. 5: Multiscale label-free photoacoustic imaging of molecular absorption.

Similar content being viewed by others

References

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

    ADS  Google Scholar 

  2. Lang, W. Nomarski differential interference-contrast microscopy. Zeiss Inf. 70, 114–120 (1968).

    Google Scholar 

  3. 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 

  4. Girshovitz, P. & Shaked, N. T. Generalized cell morphological parameters based on interferometric phase microscopy and their application to cell life cycle characterization. Biomed. Opt. Express 3, 1757–1773 (2012).

    Google Scholar 

  5. Park, Y. K., Depeursinge, C. & Popescu, G. Quantitative phase imaging in biomedicine. Nat. Photon. 12, 578–589 (2018).

    ADS  Google Scholar 

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

    Google Scholar 

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

    Google Scholar 

  8. Jin, D., Zhou, R., Yaqoob, Z. & So, P. T. C. Tomographic phase microscopy: principles and applications in bioimaging. J. Opt. Soc. Am. B 34, B64–B77 (2017).

    Google Scholar 

  9. Dardikman-Yoffe, G., Mirsky, S. K., Barnea, I. & Shaked, N. T. High-resolution 4-D acquisition of freely swimming human sperm cells without staining. Sci. Adv. 6, eaay7619 (2020).

    ADS  Google Scholar 

  10. Oldenbourg, R. Imaging: A Laboratory Manual (ed. Yuste, R.) (CSHL, 2011).

  11. Oldenbourg, R. Polarized light microscopy of spindles. Methods Cell. Biol. 61, 175–208 (1998).

    Google Scholar 

  12. Koike-Tani, M., Tani, T., Mehta, S. B., Verma, A. & Oldenbourg, R. Polarized light microscopy in reproductive and developmental biology. Mol. Reprod. Dev. 82, 548–562 (2013).

    Google Scholar 

  13. Drexler, W. & Fujimoto J. G. Optical Coherence Tomography: Technology and Applications (Springer, 2008).

  14. Leitgeb, R., Hitzenberger, C. K. & Fercher, A. F. Performance of Fourier domain vs. time domain optical coherence tomography. Opt. Express 11, 889–894 (2003).

    ADS  Google Scholar 

  15. Hillmann, D. et al. Aberration-free volumetric high-speed imaging of in vivo retina. Sci. Rep. 6, 35209 (2016).

    ADS  Google Scholar 

  16. Duker, J. S., Waheed, N. K. & Goldman, D. Handbook of Retinal OCT: Optical Coherence Tomography (Elsevier, 2013).

  17. Shemonski, N. D. et al. Computational high-resolution optical imaging of the living human retina. Nat. Photon. 9, 440–443 (2015).

    ADS  Google Scholar 

  18. Tearney, G. J. et al. Three-dimensional coronary artery microscopy by intracoronary optical frequency domain imaging. JACC Cardiovasc. Imag. 1, 752–761 (2008).

    Google Scholar 

  19. Raffel, O. C., Akasaka, T. & Jang, I.-K. Cardiac optical coherence tomography. Heart 94, 1200–1210 (2008).

    Google Scholar 

  20. Tearney, G. J. et al. In vivo endoscopic optical biopsy with optical coherence tomography. Science 276, 2037–2039 (1997).

    Google Scholar 

  21. Nolan, R. M. et al. Intraoperative optical coherence tomography for assessing human lymph nodes for metastatic cancer. BMC Cancer 16, 144 (2016).

    Google Scholar 

  22. Erickson-Bhatt, S. J. et al. Real-time imaging of the resection bed using a handheld probe to reduce incidence of microscopic positive margins in cancer surgery. Cancer Res. 75, 3706–3712 (2015).

    Google Scholar 

  23. Poneros, J. M. & Nishioka, N. S. Diagnosis of Barrett’s esophagus using optical coherence tomography. Gastrointest. Endosc. Clin. N. Am. 13, 309–323 (2013).

    Google Scholar 

  24. Dong, J. et al. Feasibility and safety of tethered capsule endomicroscopy in patients with Barrett’s esophagus in a multi-center study. Clin. Gastroenterol. Hepatol. 20, 756–765 (2022).

    Google Scholar 

  25. Sattler, E., Kästle, R. & Welzel, J. Optical coherence tomography in dermatology. J. Biomed. Opt. 18, 061224 (2013).

    ADS  Google Scholar 

  26. Gambichler, T. et al. Applications of optical coherence tomography in dermatology. J. Dermatol. Sci. 40, 85–94 (2005).

    Google Scholar 

  27. Byers, R. A. et al. Sub-clinical assessment of atopic dermatitis severity using angiographic optical coherence tomography. Biomed. Opt. Express 9, 2001–2017 (2018).

    Google Scholar 

  28. Larina, I. V. et al. Live imaging of blood flow in mammalian embryos using Doppler swept-source optical coherence tomography. J. Biomed. Opt. 13, 060506 (2008).

    ADS  Google Scholar 

  29. Singh, M. et al. Applicability, usability, and limitations of murine embryonic imaging with optical coherence tomography and optical projection tomography. Biomed. Opt. Express 7, 2295–2310 (2016).

    Google Scholar 

  30. Park, S. et al. Quantitative evaluation of the dynamic activity of HeLa cells in different viability states using dynamic full-field optical coherence microscopy. Biomed. Opt. Express 12, 6431–6441 (2021).

    Google Scholar 

  31. Mecê, P., Scholler, J., Groux, K. & Boccara, C. High-resolution in-vivo human retinal imaging using full-field OCT with optical stabilization of axial motion. Biomed. Opt. Express 11, 492–504 (2020).

    Google Scholar 

  32. Ralston, T. S., Marks, D. L., Carney, P. S. & Boppart, S. A. Interferometric synthetic aperture microscopy. Nat. Phys. 3, 129–134 (2007).

    Google Scholar 

  33. Mohler, W., Millard, A. C. & Campagnola, P. J. Second harmonic generation imaging of endogenous structural proteins. Methods 29, 97–109 (2003).

    Google Scholar 

  34. Conklin, M. W. et al. Aligned collagen is a prognostic signature for survival in human breast carcinoma. Am. J. Pathol. 178, 1221–1232 (2011).

    Google Scholar 

  35. Quinn, K. P. et al. Optical metrics of the extracellular matrix predict compositional and mechanical changes after myocardial infarction. Sci. Rep. 6, 35823 (2016).

    ADS  Google Scholar 

  36. Chu, S.-W., Tai, S.-P., Ho, C.-L., Lin, C.-H. & Sun, C.-K. High-resolution simultaneous three-photon fluorescence and third-harmonic-generation microscopy. Microsc. Res. Techn. 66, 193–197 (2005).

    Google Scholar 

  37. Tsai, M.-R., Chen, S.-Y., Shieh, D.-B., Lou, P.-J. & Sun, C.-K. In vivo optical virtual biopsy of human oral mucosa with harmonic generation microscopy. Biomed. Opt. Express 2, 2317–2328 (2011).

    Google Scholar 

  38. Walsh, A. J. et al. Classification of T-cell activation via autofluorescence lifetime imaging. Nat. Biomed. Eng. 5, 77–88 (2020).

    Google Scholar 

  39. You, S. et al. Intravital imaging by simultaneous label-free autofluorescence-multiharmonic microscopy. Nat. Commun. 9, 2125 (2018).

    ADS  Google Scholar 

  40. Skala, M. C. et al. In vivo multiphoton microscopy of NADH and FAD redox states, fluorescence lifetimes, and cellular morphology in precancerous epithelia. Proc. Natl Acad. Sci. USA 104, 19494–19499 (2007).

    ADS  Google Scholar 

  41. Liu, Z., Meng, J., Quinn, K. P. & Georgakoudi, I. Tissue imaging and quantification relying on endogenous contrast. Adv. Exp. Med. Biol. 3233, 257–288 (2021).

    Google Scholar 

  42. Becker, W., Bergmann, A. & Biskup, C. Multispectral fluorescence lifetime imaging by TCSPC. Microsc. Res. Techn. 70, 403–409 (2007).

    Google Scholar 

  43. Sorrells, J. E. et al. Computational photon counting using multi-threshold peak detection for fast fluorescence lifetime imaging microscopy. ACS Photon. 9, 2748–2755 (2022).

    Google Scholar 

  44. Bower, A. J. et al. Label-free in vivo cellular-level detection and imaging of apoptosis. J. Biophoton. 10, 143–150 (2017).

    Google Scholar 

  45. Li, Q. et al. Review of spectral imaging technology in biomedical engineering: achievements and challenges. J. Biomed. Optics 18, 100901 (2013).

    ADS  Google Scholar 

  46. Kole, M. R., Reddy, R. K., Schulmerich, M. V., Gelber, M. K. & Bhargava, R. Discrete frequency infrared microspectroscopy and imaging with a tunable quantum cascade laser. Anal. Chem. 84, 10366–10372 (2012).

    Google Scholar 

  47. Pilling, M. J., Henderson, A. & Gardner, P. Quantum cascade laser spectral histopathology: breast cancer diagnostics using high throughput chemical imaging. Anal. Chem. 89, 7348–7355 (2017).

    Google Scholar 

  48. Kuepper, C. et al. Quantum cascade laser-based infrared microscopy for label-free and automated cancer classification in tissue sections. Sci. Rep. 8, 7717 (2018).

    ADS  Google Scholar 

  49. Zhang, D. et al. Depth-resolved mid-infrared photothermal imaging of living cells and organisms with submicrometer spatial resolution. Sci. Adv. 2, e1600521 (2016).

    ADS  Google Scholar 

  50. Nedosekin, D. A., Galanzha, E. I., Dervishi, E., Biris, A. S. & Zharov, V. P. Super-resolution nonlinear photothermal microscopy. Small 10, 135–142 (2014).

    Google Scholar 

  51. Brauchle, E. & Schenke-Layland, K. Raman spectroscopy in biomedicine – non-invasive in vitro analysis of cells and extracellular matrix components in tissues. Biotechnol. J. 8, 288–297 (2013).

    Google Scholar 

  52. Krafft, C. et al. Label-free molecular imaging of biological cells and tissues by linear and nonlinear Raman spectroscopic approaches. Angew. Chem. Int. Ed. 56, 4392–4431 (2017).

    Google Scholar 

  53. Lee, K. S. et al. Raman microspectroscopy for microbiology. Nat. Rev. Methods Primers 1, 80 (2021).

    Google Scholar 

  54. Matanfack, G. A., Rüger, J., Stiebing, C., Schmitt, M. & Popp, J. Imaging the invisible—bioorthogonal Raman probes for imaging of cells and tissues. J. Biophoton. 13, e202000129 (2020).

    Google Scholar 

  55. Zumbusch, A., Holtom, G. R. & Xie, X. S. Three-dimensional vibrational imaging by coherent anti-Stokes Raman scattering. Phys. Rev. Lett. 82, 4142–4145 (1999).

    ADS  Google Scholar 

  56. Tu, H. et al. Concurrence of extracellular vesicle enrichment and metabolic switch visualized label-free in the tumor microenvironment. Sci. Adv. 3, e1600675 (2017).

    ADS  Google Scholar 

  57. Liu, Y. et al. Label-free molecular profiling for identification of biomarkers in carcinogenesis using multimodal multiphoton imaging. Quant. Imag. Med. Surg. 9, 742–756 (2019).

    Google Scholar 

  58. Freudiger, C. W. et al. Label-free biomedical imaging with high sensitivity by stimulated Raman scattering microscopy. Science 322, 1857–1861 (2008).

    ADS  Google Scholar 

  59. Cheng, J.-X., Min, W., Ozeki, Y. & Polli, D. Stimulated Raman Scattering Microscopy: Techniques and Applications (Elsevier, 2022).

  60. Wang, L. V. & Hu, S. Photoacoustic tomography: in vivo imaging from organelles to organs. Science 335, 1458–1462 (2012).

    ADS  Google Scholar 

  61. Wang, X. D. et al. Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain. Nat. Biotechnol. 21, 803–806 (2003).

    Google Scholar 

  62. Siphanto, R. I. et al. Serial noninvasive photoacoustic imaging of neovascularization in tumor angiogenesis. Opt. Express 13, 89–95 (2005).

    ADS  Google Scholar 

  63. Laufer, J., Delpy, D., Elwell, C. & Beard, P. Quantitative spatially resolved measurement of tissue chromophore concentrations using photoacoustic spectroscopy: application to the measurement of blood oxygenation and haemoglobin concentration. Phys. Med. Biol. 52, 141–168 (2007).

    Google Scholar 

  64. Zhang, H. F., Maslov, K., Stoica, G. & Wang, L. V. Functional photoacoustic microscopy for high-resolution and noninvasive in vivo imaging. Nat. Biotechnol. 24, 848–851 (2006).

    Google Scholar 

  65. Xu, M. H. & Wang, L. V. Universal back-projection algorithm for photoacoustic computed tomography. Phys. Rev. E 71, 016706 (2005).

    ADS  Google Scholar 

  66. Nagae, K. et al. Real-time 3D photoacoustic visualization system with a wide field of view for imaging human limbs. F1000Research 7, 1813 (2018).

    Google Scholar 

  67. Lin, L. et al. Single-breath-hold photoacoustic computed tomography of the breast. Nat. Commun. 9, 2352 (2018).

    ADS  Google Scholar 

  68. Dantuma, M. et al. Fully three-dimensional sound speed-corrected multi-wavelength photoacoustic breast tomography. Preprint at https://arxiv.org/abs/2308.06754 (2023).

  69. Na, S. et al. Massively parallel functional photoacoustic computed tomography of the human brain. Nat. Biomed. Eng. 6, 584–592 (2022).

    Google Scholar 

  70. Wong, T. T. et al. Fast label-free multilayered histology-like imaging of human breast cancer by photoacoustic microscopy. Sci. Adv. 3, e1602168 (2017).

    ADS  Google Scholar 

  71. Li, L. et al. Single-impulse panoramic photoacoustic computed tomography of small-animal whole-body dynamics at high spatiotemporal resolution. Nat. Biomed. Eng. 1, 0071 (2017).

    Google Scholar 

  72. Sun, Y. et al. Detection of weak near-infrared optical imaging signals under ambient light by optical parametric amplification. Opt. Lett. 44, 4391–4394 (2019).

    ADS  Google Scholar 

  73. Schürmann, M., Scholze, J., Müller, P., Guck, J. & Chan, C. J. Cell nuclei have lower refractive index and mass density than cytoplasm. J. Biophoton. 9, 1068–1076 (2016).

    Google Scholar 

  74. Rivenson, Y. et al. Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning. Nat. Biomed. Eng. 3, 466–477 (2019).

    Google Scholar 

  75. Nygate, Y. N. et al. Holographic virtual staining of individual biological cells. Proc. Natl Acad. Sci. USA 117, 9223–9231 (2020).

    ADS  Google Scholar 

  76. Kandel, M. E. et al. Phase imaging with computational specificity (PICS) for measuring dry mass changes in sub-cellular compartments. Nat. Commun. 11, 6256 (2020).

    ADS  Google Scholar 

  77. You, S., Chaney, E. J., Tu, H., Sinha, S. & Boppart, S. A. Label-free deep profiling of the tumor microenvironment. Cancer Res. 81, 2534–2544 (2021).

    Google Scholar 

  78. Krafft, C. & Popp, J. Opportunities of optical and spectral technologies in intraoperative histopathology. Optica 10, 214–231 (2023).

    ADS  Google Scholar 

  79. Pradhan, P. et al. Computational tissue staining of non-linear multimodal imaging using supervised and unsupervised deep learning. Biomed. Opt. Express 12, 2280–2298 (2021).

    Google Scholar 

  80. You, S. et al. Real-time intraoperative diagnosis by deep neural network driven multiphoton virtual histology. Precis. Oncol. 3, 33 (2019).

    Google Scholar 

  81. Hell, S. W. et al. The 2015 super-resolution microscopy roadmap. J. Phys. D 48, 443001 (2015).

    Google Scholar 

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

    ADS  Google Scholar 

  83. Bi, Y. et al. Near-resonance enhanced label-free stimulated Raman scattering microscopy with spatial resolution near 130 nm. Light Sci. Appl. 7, 81 (2018).

    ADS  Google Scholar 

  84. Gong, L., Zheng, W., Ma, Y. & Huang, Z. Higher-order coherent anti-Stokes Raman scattering microscopy realizes label-free super-resolution vibrational imaging. Nat. Photon. 14, 115–122 (2020).

    ADS  Google Scholar 

  85. Danielli, A. et al. Label-free photoacoustic nanoscopy. J. Biomed. Opt. 19, 086006 (2014).

    ADS  Google Scholar 

  86. Fu, P. et al. Super-resolution imaging of non-fluorescent molecules by photothermal relaxation localization microscopy. Nat. Photon. 17, 330–337 (2023).

    ADS  Google Scholar 

  87. Lindfors, K., Kalkbrenner, T., Stoller, P. & Sandoghdar, V. Detection and spectroscopy of gold nanoparticles using supercontinuum white light confocal microscopy. Phys. Rev. Lett. 93, 037401 (2004).

    ADS  Google Scholar 

  88. Foley, E. D. B., Kushwah, M. S., Young, G. & Kukura, P. Mass photometry enables label-free tracking and mass measurement of single proteins on lipid bilayers. Nat. Methods 18, 1247–1252 (2021).

    Google Scholar 

  89. Heermann, T., Steiert, F., Ramm, B., Hundt, N. & Schwille, P. Mass-sensitive particle tracking to elucidate the membrane-associated MinDE reaction cycle. Nat. Methods 18, 1239–1246 (2021).

    Google Scholar 

  90. Sun, Y. et al. Intraoperative visualization of the tumor microenvironment and quantification of extracellular vesicles by label-free nonlinear imaging. Sci. Adv. 4, eaau5603 (2018).

    ADS  Google Scholar 

  91. Monroy, G. M., Won, J., Spillman, D. R., Dsouza, R. & Boppart, S. A. Clinical translation of handheld optical coherence tomography: practical considerations and recent advances. J. Biomed. Optics 22, 121715 (2017).

    ADS  Google Scholar 

  92. Jermyn, M. et al. Intraoperative brain cancer detection with Raman spectroscopy in humans. Sci. Transl. Med. 7, 274ra19 (2015).

    Google Scholar 

  93. Pshenay-Severin, E. et al. Multimodal nonlinear endomicroscopic imaging probe using a double-core double-clad fiber and focus-combining micro-optical concept. Light Sci. Appl. 10, 207 (2021).

    ADS  Google Scholar 

  94. Rank, E. A. et al. Toward optical coherence tomography on a chip: in vivo three-dimensional human retinal imaging using photonic integrated circuit-based arrayed waveguide gratings. Light Sci. Appl. 10, 6 (2021).

    ADS  Google Scholar 

  95. Wuytens, P. C., Skirtach, A. G. & Baets, R. On-chip surface-enhanced Raman spectroscopy using nanosphere-lithography patterned antennas on silicon nitride waveguides. Opt. Express 25, 12926–12934 (2017).

    ADS  Google Scholar 

  96. Yu, N. & Capasso, F. Flat optics with designer metasurfaces. Nat. Mater. 13, 139–150 (2014).

    ADS  Google Scholar 

  97. Neshev, D. & Aharonovich, I. Optical metasurfaces: new generation building blocks for multi-functional optics. Light Sci. Appl. 7, 58 (2018).

    ADS  Google Scholar 

  98. Meyer, T. et al. A compact microscope setup for multimodal nonlinear imaging in clinics and its application to disease diagnostics. Analyst 138, 4048–4057 (2013).

    ADS  Google Scholar 

  99. You, S. et al. Label-free visualization and characterization of extracellular vesicles in breast cancer. Proc. Natl Acad. Sci. USA 116, 24012–24018 (2019).

    ADS  Google Scholar 

  100. Iyer, R. R. et al. Ultra-parallel label-free optophysiology of neural activity. iScience 25, 104307 (2022).

    ADS  Google Scholar 

  101. Bower, A. J. et al. High-speed imaging of transient metabolic dynamics using two-photon fluorescence lifetime imaging microscopy. Optica 5, 1290–1296 (2018).

    ADS  Google Scholar 

  102. Tehrani, K.F., Park, J., Renteria, C. & Boppart, S.A. Label-free identification of Alzheimer’s disease plaques using multiple co-registered nonlinear optical biomarkers. In Clinical and Translational Neurophotonics, SPIE Photonics West BiOS 12364-2 (SPIE, 2023).

  103. Lai, C. et al. Design and test of a rigid endomicroscopic system for multimodal imaging and femtosecond laser ablation. J. Biomed. Optics https://doi.org/10.1117/1.JBO.28.6.066004 (2023).

  104. Chernavskaia, O. et al. Beyond endoscopic assessment in inflammatory bowel disease: real-time histology of disease activity by non-linear multimodal imaging. Sci. Rep. 6, 29239 (2016).

    ADS  Google Scholar 

  105. Fitzgerald, S. et al. Multimodal Raman spectroscopy and optical coherence tomography for biomedical analysis. J. Biophoton. https://doi.org/10.1002/jbio.202200231 (2023).

  106. Kalashnikov, D. A., Paterova, A. V., Kulik, S. P. & Krivitsky, L. A. Infrared spectroscopy with visible light. Nat. Photon. 10, 98–101 (2016).

    ADS  Google Scholar 

  107. Barreto Lemos, G. et al. Quantum imaging with undetected photons. Nature 512, 409–412 (2014).

    ADS  Google Scholar 

Download references

Acknowledgements

We acknowledge the support of the following grants: Horizon2020 ERC grant (678316) (PI: N.T.S.). NIH Center for Label-free Imaging and Multiscale Biophotonics (CLIMB) at the University of Illinois Urbana-Champaign (http://climb.beckman.illinois.edu) P41 EB031772 and NIH grant numbers R01 CA241618 and R01 CA213149 (PI: S.A.B.). NIH grant numbers R01 NS102213, U01 EB029823 (BRAIN Initiative), R35 CA220436 (Outstanding Investigator Award), and R01 EB028277 (PI: L.V.W.).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Natan T. Shaked.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Photonics thanks Paul Campagnola, Ping Wang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shaked, N.T., Boppart, S.A., Wang, L.V. et al. Label-free biomedical optical imaging. Nat. Photon. 17, 1031–1041 (2023). https://doi.org/10.1038/s41566-023-01299-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41566-023-01299-6

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing