- Physical Review Journals
All JournalsPhysics Magazine

Physical Review Applied

Reuse & Permissions

It is not necessary to obtain permission to reuse this article or its components as it is available under the terms of the Creative Commons Attribution 4.0 International license. This license permits unrestricted use, distribution, and reproduction in any medium, provided attribution to the author(s) and the published article's title, journal citation, and DOI are maintained. Please note that some figures may have been included with permission from other third parties. It is your responsibility to obtain the proper permission from the rights holder directly for these figures.

Export citation

Export citation

Choose format for download:

Download Citation
  • Open Access

Enhancing the speed of direct volumetric imaging through annular illumination and spatial coherence of light

Gianlorenzo Massaro1,2,*, Adalberto Brunetti1, Francesco V. Pepe1,2, and Milena D’Angelo1,2

  • *Contact author: gianlorenzo.massaro@uniba.it
PDF

Phys. Rev. Applied 25, 024088 – Published 27 February, 2026

DOI: https://doi.org/10.1103/1z4w-8425

Abstract

We propose and demonstrate a direct volumetric imaging method based on spatial coherence of light and sequential illumination from pointlike sources distributed along a ring. We prove that when the source geometry restricts illumination to high-angle modes matching the system numerical aperture, linear annular illumination achieves the same lateral resolution and similar axial sectioning as planar full-disk illumination, while offering the advantage of a threefold faster acquisition and an even lighter computational demand. The proposed approach offers a simplified and efficient alternative to conventional light-field and computational imaging, opening new paths for fast, cost-effective, real-time volumetric imaging and three-dimensional microscopy.

View figure in article

Physics Subject Headings (PhySH)

Article Text

References (38)

  1. D. B. Murphy and M. W. Davidson, Fundamentals of Light Microscopy and Electronic Imaging (Wiley-Liss, Hoboken, New Jersey, USA, 2013).
  2. W. R. Zipfel, R. M. Williams, and W. W. Webb, Three-dimensional imaging of biological tissue by multiphoton microscopy, Nat. Biotechnol. 21, 1369 (2003).
  3. J. R. Swedlow and M. Platani, Three-dimensional microscopy: Image acquisition and processing, Microsc. Res. Tech. 62, 127 (2003).
  4. R. Ng, in Stanford University Computer Science Tech Report CSTR (2005), https://graphics.stanford.edu/papers/lfcamera/.
  5. M. Levoy, R. Ng, A. Adams, M. Footer, and M. Horowitz, Light field microscopy, ACM Trans. Graph. (TOG) 25, 924 (2006).
  6. M. Broxton, L. Grosenick, S. Yang, N. Cohen, A. Andalman, K. Deisseroth, and M. Levoy, Wave optics theory and 3-D deconvolution for the light field microscope, Opt. Express 21, 25418 (2013).
  7. R. Prevedel, Y.-G. Yoon, M. Hoffmann, N. Pak, G. Wetzstein, T. Schrödel, R. Raskar, M. Zimmer, E. S. Boyden, and A. Vaziri, Simultaneous whole-animal 3D imaging of neuronal activity using light-field microscopy, Nat. Methods 11, 727 (2014).
  8. N. Wagner, N. Norlin, J. Gierten, G. de Medeiros, B. Balász, J. Wittbrodt, L. Hufnager, and R. Prevedel, Instantaneous isotropic volumetric imaging of fast biological processes, Nat. Methods 16, 497 (2019).
  9. P. A. Stokseth, Properties of a defocused optical system, J. Opt. Soc. Am. 59, 1314 (1969).
  10. C. Guo and G. Barbastathis, Understanding tradeoffs in light field microscopy, Optica 7, 1128 (2020).
  11. R. Prevedel, Y.-G. Yoon, M. Hoffmann, N. Pak, G. Wetzstein, S. Kato, T. Schrödel, R. Raskar, M. Zimmer, E. S. Boyden, and A. Vaziri, Performance tradeoffs in light field microscopy, Nat. Methods 11, 727 (2014).
  12. B. Lin, Y. Tian, Y. Zhang, Z. Zhu, and D. Wang, Deep learning methods for high-resolution microscale light field image reconstruction: A survey, Front. Bioeng. Biotechnol. 12, 1500270 (2024).
  13. Z. Wang, L. Zhu, H. Zhang, G. Li, C. Yi, Y. Li, Y. Yang, Y. Ding, M. Zhen, S. Gao, T. K. Hsiai, and P. Fei, Real-time volumetric reconstruction of biological dynamics with light-field microscopy and deep learning, Nat. Methods 18, 551 (2021).
  14. J. Rodenburg and A. Maiden, in Springer Handbook of Microscopy (Springer International Publishing, Cham, Switzerland, 2019), p. 819.
  15. G. Zheng, R. Horstmeyer, and C. Yang, Wide-field, high-resolution Fourier ptychographic microscopy, Nat. Photonics 7, 739 (2013).
  16. U. Schnars, C. Falldorf, J. Watson, and W. Jüptner, Digital Holography and Wavefront Sensing, Digital holography (2015).
  17. M. G. Gustafsson, Surpassing the lateral resolution limit by a factor of two using structured illumination microscopy, J. Microsc. 198, 82 (2000).
  18. R. Heintzmann and M. G. L. Gustafsson, Subdiffraction resolution in continuous samples, Nat. Photonics 3, 362 (2009).
  19. R. Fiolka, L. Shao, E. H. Rego, M. W. Davidson, and M. G. L. Gustafsson, Time-lapse two-color 3D imaging of live cells with doubled resolution using structured illumination, Proc. Natl. Acad. Sci. 109, 5311 (2012).
  20. X. Li, et al., Three-dimensional structured illumination microscopy with enhanced axial resolution, Nat. Biotechnol. 41, 1307 (2023).
  21. G. Massaro, B. Barile, G. Scarcelli, F. V. Pepe, G. P. Nicchia, and M. D’Angelo, Direct 3D imaging through spatial coherence of light, Laser Photonics Rev. 18, 2301155 (2024).
  22. K. Guo, S. Dong, and G. Zheng, Fourier ptychographic microscopy using annular illumination, Opt. Lett. 41, 760 (2016).
  23. P. Li and G. Zheng, Annular illumination Fourier ptychography for high-resolution phase imaging, Optica 6, 67 (2019).
  24. G. Massaro, Assessing the 3D resolution of refocused correlation plenoptic images using a general-purpose image quality estimator, Eur. Phys. J. Plus 139, 727 (2024).
  25. E. Hecht, in Optics (Pearson, San Francisco, California, USA, 2012), chapter 12.
  26. J. W. Goodman, in Introduction to Fourier Optics, edited by J. W. Goodman (Roberts & Co. Publishers, Englewood, CO, 2005), Vol. 1, 3rd ed.
  27. G. Massaro, S. de Gioia, A. Brunetti, F. V. Pepe, and M. D’angelo, Two-point resolution of a defocused imaging system based on spatially coherent illumination, Photonics 11, 1203 (2024).
  28. G. Massaro and M. D’Angelo, Characterization of defocused coherent imaging systems with periodic objects, Sensors 24, 6885 (2024).
  29. F. Andersson, M. Carlsson, and V. V. Nikitin, Fast algorithms and efficient GPU implementations for the radon transform and the back-projection operator represented as convolution operators, SIAM J. Imaging Sci. 9, 637 (2016).
  30. H. Gross, F. Blechinger, and B. Achtner, Handbook of Optical Systems (WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim, Germany, 2008), Vol. 4.
  31. G. Massaro, Analytical form of the refocused images from correlation plenoptic imaging, Opt. Express 32, 35755 (2024).
  32. G. Massaro, P. Mos, S. Vasiukov, F. Di Lena, F. Scattarella, F. V. Pepe, A. Ulku, D. Giannella, E. Charbon, C. Bruschini, and M. D’Angelo, Correlated-photon imaging at 10 volumetric images per second, Sci. Rep. 13, 12813 (2023).
  33. G. Massaro, D. Giannella, A. Scagliola, F. Di Lena, G. Scarcelli, A. Garuccio, F. V. Pepe, and M. D’Angelo, Light-field microscopy with correlated beams for high-resolution volumetric imaging, Sci. Rep. 12, 16823 (2022).
  34. B. I. Erkmen and J. H. Shapiro, Signal-to-noise ratio of Gaussian-state ghost imaging, Phys. Rev. A—At., Mol. Opt. Phys. 79, 023833 (2009).
  35. G. Massaro, G. Scala, M. D’Angelo, and F. V. Pepe, Comparative analysis of signal-to-noise ratio in correlation plenoptic imaging architectures, Eur. Phys. J. Plus 137, 1123 (2022).
  36. F. Scattarella, D. Diacono, A. Monaco, N. Amoroso, L. Bellantuono, G. Massaro, F. V. Pepe, S. Tangaro, R. Bellotti, and M. D’Angelo, Deep learning approach for denoising low-SNR correlation plenoptic images, Sci. Rep. 13, 19645 (2023).
  37. I. Petrelli, F. Santoro, G. Massaro, F. Scattarella, F. V. Pepe, F. Mazzia, M. Ieronymaki, G. Filios, D. Mylonas, N. Pappas, C. Abbattista, and M. D’Angelo, Compressive sensing-based correlation plenoptic imaging, Front. Phys. 11, 1287740 (2023).
  38. Data repository. https://www.myqnapcloud.com/smartshare/7931f6i62m597s0v142u106b_9837gil4236920s11svyw58xdcd0f9e5.

Outline

Information

Phys. Rev. Applied 25, 024088– Published 27 February, 2026
  • Received 7 August 2025
  • Revised 26 November 2025
  • Accepted 9 January 2026
Crossmark - Check for updates button
Creative Commons Logo

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.

Published by the American Physical Society

Sign In to Your Journals Account

Filter

Filter

Article Lookup

Enter a citation