Abstract

We demonstrate a new computational illumination technique that achieves a large space–bandwidth–time product, for quantitative phase imaging of unstained live samples in vitro. Microscope lenses can have either a large field of view (FOV) or high resolution, and not both. Fourier ptychographic microscopy (FPM) is a new computational imaging technique that circumvents this limit by fusing information from multiple images taken with different illumination angles. The result is a gigapixel-scale image having both a wide FOV and high resolution, i.e., a large space–bandwidth product. FPM has enormous potential for revolutionizing microscopy and has already found application in digital pathology. However, it suffers from long acquisition times (of the order of minutes), limiting throughput. Faster capture times would not only improve the imaging speed, but also allow studies of live samples, where motion artifacts degrade results. In contrast to fixed (e.g., pathology) slides, live samples are continuously evolving at various spatial and temporal scales. Here, we present a new source coding scheme, along with real-time hardware control, to achieve 0.8 NA resolution across a 4× FOV with subsecond capture times. We propose an improved algorithm and a new initialization scheme, which allow robust phase reconstruction over long time-lapse experiments. We present the first FPM results for both growing and confluent in vitro cell cultures, capturing videos of subcellular dynamical phenomena in popular cell lines undergoing division and migration. Our method opens up FPM to applications with live samples, for observing rare events in both space and time.

© 2015 Optical Society of America

Full Article  |  PDF Article
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References

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2015 (5)

W. Luo, A. Greenbaum, Y. Zhang, and A. Ozcan, “Synthetic aperture-based on-chip microscopy,” Light 4, e261 (2015).
[Crossref]

G. Zheng, R. Horstmeyer, and C. Yang, “Corrigendum: wide-field, high-resolution Fourier ptychographic microscopy,” Nat. Photonics 9, 621 (2015).
[Crossref]

Z. F. Phillips, M. V. D’Ambrosio, L. Tian, J. J. Rulison, H. S. Patel, N. Sadras, A. V. Gande, N. A. Switz, D. A. Fletcher, and L. Waller, “Multi-contrast imaging and digital refocusing on a mobile microscope with a domed led array,” PLoS ONE 10, e0124938 (2015).
[Crossref]

L. Tian and L. Waller, “3D intensity and phase imaging from light field measurements in an LED array microscope,” optica 2, 104–111 (2015).
[Crossref]

L. Tian and L. Waller, “Quantitative differential phase contrast imaging in an LED array microscope,” Opt. Express 23, 11394–11403 (2015).
[Crossref]

2014 (6)

X. Ou, G. Zheng, and C. Yang, “Embedded pupil function recovery for Fourier ptychographic microscopy,” Opt. Express 22, 4960–4972 (2014).
[Crossref]

Z. Jingshan, R. A. Claus, J. Dauwels, L. Tian, and L. Waller, “Transport of intensity phase imaging by intensity spectrum fitting of exponentially spaced defocus planes,” Opt. Express 22, 10661–10674 (2014).
[Crossref]

L. Tian, X. Li, K. Ramchandran, and L. Waller, “Multiplexed coded illumination for Fourier ptychography with an LED array microscope,” Biomed. Opt. Express 5, 2376–2389 (2014).
[Crossref]

A. Greenbaum, Y. Zhang, A. Feizi, P.-L. Chung, W. Luo, S. R. Kandukuri, and A. Ozcan, “Wide-field computational imaging of pathology slides using lens-free on-chip microscopy,” Sci. Transl. Med. 6, 267ra175 (2014).
[Crossref]

Y. Shechtman, A. Beck, and Y. Eldar, “GESPAR: efficient phase retrieval of sparse signals,” IEEE Trans. Signal Process. 62, 928–938 (2014).
[Crossref]

K. Wicker and R. Heintzmann, “Resolving a misconception about structured illumination,” Nat. Photonics 8, 342–344 (2014).
[Crossref]

2013 (2)

G. Zheng, R. Horstmeyer, and C. Yang, “Wide-field, high-resolution Fourier ptychographic microscopy,” Nat. Photonics 7, 739–745 (2013).
[Crossref]

X. Ou, R. Horstmeyer, C. Yang, and G. Zheng, “Quantitative phase imaging via Fourier ptychographic microscopy,” Opt. Lett. 38, 4845–4848 (2013).
[Crossref]

2012 (2)

A. Orth and K. Crozier, “Microscopy with microlens arrays: high throughput, high resolution and light-field imaging,” Opt. Express 20, 13522–13531 (2012).
[Crossref]

A. Greenbaum, W. Luo, T.-W. Su, Z. Göröcs, L. Xue, S. O. Isikman, A. F. Coskun, O. Mudanyali, and A. Ozcan, “Imaging without lenses: achievements and remaining challenges of wide-field on-chip microscopy,” Nat. Methods 9, 889–895 (2012).
[Crossref]

2011 (5)

M. R. Costa, F. Ortega, M. S. Brill, R. Beckervordersandforth, C. Petrone, T. Schroeder, M. Götz, and B. Berninger, “Continuous live imaging of adult neural stem cell division and lineage progression in vitro,” Development 138, 1057–1068 (2011).
[Crossref]

N. Rimon and M. Schuldiner, “Getting the whole picture: combining throughput with content in microscopy,” J. Cell Sci. 124, 3743–3751 (2011).
[Crossref]

G. Zheng, S. A. Lee, Y. Antebi, M. B. Elowitz, and C. Yang, “The ePetri dish, an on-chip cell imaging platform based on subpixel perspective sweeping microscopy (SPSM),” Proc. Natl. Acad. Sci. USA 108, 16889–16894 (2011).
[Crossref]

M. Mir, Z. Wang, Z. Shen, M. Bednarz, R. Bashir, I. Golding, S. G. Prasanth, and G. Popescu, “Optical measurement of cycle-dependent cell growth,” Proc. Natl. Acad. Sci. USA 108, 13124–13129 (2011).
[Crossref]

A. E. Tippie, A. Kumar, and J. R. Fienup, “High-resolution synthetic-aperture digital holography with digital phase and pupil correction,” Opt. Express 19, 12027–12038 (2011).
[Crossref]

2010 (2)

T. Gutzler, T. R. Hillman, S. A. Alexandrov, and D. D. Sampson, “Coherent aperture-synthesis, wide-field, high-resolution holographic microscopy of biological tissue,” Opt. Lett. 35, 1136–1138 (2010).
[Crossref]

A. R. Cohen, F. L. Gomes, B. Roysam, and M. Cayouette, “Computational prediction of neural progenitor cell fates,” Nat. Methods 7, 213–218 (2010).
[Crossref]

2009 (4)

S. Mehta and C. Sheppard, “Quantitative phase-gradient imaging at high resolution with asymmetric illumination-based differential phase contrast,” Opt. Lett. 34, 1924–1926 (2009).
[Crossref]

K. Goda, K. Tsia, and B. Jalali, “Serial time-encoded amplified imaging for real-time observation of fast dynamic phenomena,” Nature 458, 1145–1149 (2009).
[Crossref]

A. M. Maiden and J. M. Rodenburg, “An improved ptychographical phase retrieval algorithm for diffractive imaging,” Ultramicroscopy 109, 1256–1262 (2009).
[Crossref]

P. Thibault, M. Dierolf, O. Bunk, A. Menzel, and F. Pfeiffer, “Probe retrieval in ptychographic coherent diffractive imaging,” Ultramicroscopy 109, 338–343 (2009).
[Crossref]

2008 (4)

O. Bunk, M. Dierolf, S. Kynde, I. Johnson, O. Marti, and F. Pfeiffer, “Influence of the overlap parameter on the convergence of the ptychographical iterative engine,” Ultramicroscopy 108, 481–487 (2008).
[Crossref]

G. Popescu, Y. Park, N. Lue, C. Best-Popescu, L. Deflores, R. R. Dasari, M. S. Feld, and K. Badizadegan, “Optical imaging of cell mass and growth dynamics,” Am. J. Physiol. 295, C538–C544 (2008).
[Crossref]

E. J. Candès and M. B. Wakin, “An introduction to compressive sampling,” IEEE Signal Process. Mag. 25(2), 21–30 (2008).
[Crossref]

M. Guizar-Sicairos and J. R. Fienup, “Phase retrieval with transverse translation diversity: a nonlinear optimization approach,” Opt. Express 16, 7264–7278 (2008).
[Crossref]

2006 (2)

A. E. Carpenter, T. R. Jones, M. R. Lamprecht, C. Clarke, I. H. Kang, O. Friman, D. A. Guertin, J. H. Chang, R. A. Lindquist, J. Moffat, P. Golland, and D. M. Sabatini, “CellProfiler: image analysis software for identifying and quantifying cell phenotypes,” Genome Biol. 7, R100 (2006).
[Crossref]

P. Lang, K. Yeow, A. Nichols, and A. Scheer, “Cellular imaging in drug discovery,” Nat. Rev. Drug Discov. 5, 343–356 (2006).
[Crossref]

2004 (1)

J. M. Rodenburg and H. M. Faulkner, “A phase retrieval algorithm for shifting illumination,” Appl. Phys. Lett. 85, 4795–4797 (2004).
[Crossref]

2002 (1)

E. D. Barone-Nugent, A. Barty, and K. A. Nugent, “Quantitative phase-amplitude microscopy I: optical microscopy,” J. Microsc. 206, 194–203 (2002).
[Crossref]

2000 (2)

T. Otaki, “Artifact halo reduction in phase contrast microscopy using apodization,” Opt. Rev. 7, 119–122 (2000).
[Crossref]

M. G. Gustafsson, “Surpassing the lateral resolution limit by a factor of two using structured illumination microscopy,” J. Microsc. 198, 82–87 (2000).
[Crossref]

1995 (1)

M. R. Boyd and K. D. Paull, “Some practical considerations and applications of the national cancer institute in vitro anticancer drug discovery screen,” Drug Develop. Res. 34, 91–109 (1995).
[Crossref]

1986 (1)

1984 (1)

D. Hamilton and C. Sheppard, “Differential phase contrast in scanning optical microscopy,” J. Microsc. 133, 27–39 (1984).
[Crossref]

1982 (1)

1977 (1)

H. Rose, “Nonstandard imaging methods in electron microscopy,” Ultramicroscopy 2, 251–267 (1977).
[Crossref]

1967 (1)

1966 (1)

1952 (1)

R. Barer, “Interference microscopy and mass determination,” Nature 169, 366–367 (1952).
[Crossref]

Alexandrov, S. A.

Antebi, Y.

G. Zheng, S. A. Lee, Y. Antebi, M. B. Elowitz, and C. Yang, “The ePetri dish, an on-chip cell imaging platform based on subpixel perspective sweeping microscopy (SPSM),” Proc. Natl. Acad. Sci. USA 108, 16889–16894 (2011).
[Crossref]

Badizadegan, K.

G. Popescu, Y. Park, N. Lue, C. Best-Popescu, L. Deflores, R. R. Dasari, M. S. Feld, and K. Badizadegan, “Optical imaging of cell mass and growth dynamics,” Am. J. Physiol. 295, C538–C544 (2008).
[Crossref]

Barer, R.

R. Barer, “Interference microscopy and mass determination,” Nature 169, 366–367 (1952).
[Crossref]

Barone-Nugent, E. D.

E. D. Barone-Nugent, A. Barty, and K. A. Nugent, “Quantitative phase-amplitude microscopy I: optical microscopy,” J. Microsc. 206, 194–203 (2002).
[Crossref]

Barty, A.

E. D. Barone-Nugent, A. Barty, and K. A. Nugent, “Quantitative phase-amplitude microscopy I: optical microscopy,” J. Microsc. 206, 194–203 (2002).
[Crossref]

Bashir, R.

M. Mir, Z. Wang, Z. Shen, M. Bednarz, R. Bashir, I. Golding, S. G. Prasanth, and G. Popescu, “Optical measurement of cycle-dependent cell growth,” Proc. Natl. Acad. Sci. USA 108, 13124–13129 (2011).
[Crossref]

Beck, A.

Y. Shechtman, A. Beck, and Y. Eldar, “GESPAR: efficient phase retrieval of sparse signals,” IEEE Trans. Signal Process. 62, 928–938 (2014).
[Crossref]

Beckervordersandforth, R.

M. R. Costa, F. Ortega, M. S. Brill, R. Beckervordersandforth, C. Petrone, T. Schroeder, M. Götz, and B. Berninger, “Continuous live imaging of adult neural stem cell division and lineage progression in vitro,” Development 138, 1057–1068 (2011).
[Crossref]

Bednarz, M.

M. Mir, Z. Wang, Z. Shen, M. Bednarz, R. Bashir, I. Golding, S. G. Prasanth, and G. Popescu, “Optical measurement of cycle-dependent cell growth,” Proc. Natl. Acad. Sci. USA 108, 13124–13129 (2011).
[Crossref]

Berninger, B.

M. R. Costa, F. Ortega, M. S. Brill, R. Beckervordersandforth, C. Petrone, T. Schroeder, M. Götz, and B. Berninger, “Continuous live imaging of adult neural stem cell division and lineage progression in vitro,” Development 138, 1057–1068 (2011).
[Crossref]

Best-Popescu, C.

G. Popescu, Y. Park, N. Lue, C. Best-Popescu, L. Deflores, R. R. Dasari, M. S. Feld, and K. Badizadegan, “Optical imaging of cell mass and growth dynamics,” Am. J. Physiol. 295, C538–C544 (2008).
[Crossref]

Boyd, M. R.

M. R. Boyd and K. D. Paull, “Some practical considerations and applications of the national cancer institute in vitro anticancer drug discovery screen,” Drug Develop. Res. 34, 91–109 (1995).
[Crossref]

Brill, M. S.

M. R. Costa, F. Ortega, M. S. Brill, R. Beckervordersandforth, C. Petrone, T. Schroeder, M. Götz, and B. Berninger, “Continuous live imaging of adult neural stem cell division and lineage progression in vitro,” Development 138, 1057–1068 (2011).
[Crossref]

Bunk, O.

P. Thibault, M. Dierolf, O. Bunk, A. Menzel, and F. Pfeiffer, “Probe retrieval in ptychographic coherent diffractive imaging,” Ultramicroscopy 109, 338–343 (2009).
[Crossref]

O. Bunk, M. Dierolf, S. Kynde, I. Johnson, O. Marti, and F. Pfeiffer, “Influence of the overlap parameter on the convergence of the ptychographical iterative engine,” Ultramicroscopy 108, 481–487 (2008).
[Crossref]

Candès, E. J.

E. J. Candès and M. B. Wakin, “An introduction to compressive sampling,” IEEE Signal Process. Mag. 25(2), 21–30 (2008).
[Crossref]

E. J. Candès, X. Li, and M. Soltanolkotabi, “Phase retrieval via Wirtinger flow: theory and algorithms,” arXiv:1407.1065 (2014).

Carpenter, A. E.

A. E. Carpenter, T. R. Jones, M. R. Lamprecht, C. Clarke, I. H. Kang, O. Friman, D. A. Guertin, J. H. Chang, R. A. Lindquist, J. Moffat, P. Golland, and D. M. Sabatini, “CellProfiler: image analysis software for identifying and quantifying cell phenotypes,” Genome Biol. 7, R100 (2006).
[Crossref]

Cayouette, M.

A. R. Cohen, F. L. Gomes, B. Roysam, and M. Cayouette, “Computational prediction of neural progenitor cell fates,” Nat. Methods 7, 213–218 (2010).
[Crossref]

Chang, J. H.

A. E. Carpenter, T. R. Jones, M. R. Lamprecht, C. Clarke, I. H. Kang, O. Friman, D. A. Guertin, J. H. Chang, R. A. Lindquist, J. Moffat, P. Golland, and D. M. Sabatini, “CellProfiler: image analysis software for identifying and quantifying cell phenotypes,” Genome Biol. 7, R100 (2006).
[Crossref]

Chung, P.-L.

A. Greenbaum, Y. Zhang, A. Feizi, P.-L. Chung, W. Luo, S. R. Kandukuri, and A. Ozcan, “Wide-field computational imaging of pathology slides using lens-free on-chip microscopy,” Sci. Transl. Med. 6, 267ra175 (2014).
[Crossref]

Clarke, C.

A. E. Carpenter, T. R. Jones, M. R. Lamprecht, C. Clarke, I. H. Kang, O. Friman, D. A. Guertin, J. H. Chang, R. A. Lindquist, J. Moffat, P. Golland, and D. M. Sabatini, “CellProfiler: image analysis software for identifying and quantifying cell phenotypes,” Genome Biol. 7, R100 (2006).
[Crossref]

Claus, R. A.

Cohen, A. R.

A. R. Cohen, F. L. Gomes, B. Roysam, and M. Cayouette, “Computational prediction of neural progenitor cell fates,” Nat. Methods 7, 213–218 (2010).
[Crossref]

Coskun, A. F.

A. Greenbaum, W. Luo, T.-W. Su, Z. Göröcs, L. Xue, S. O. Isikman, A. F. Coskun, O. Mudanyali, and A. Ozcan, “Imaging without lenses: achievements and remaining challenges of wide-field on-chip microscopy,” Nat. Methods 9, 889–895 (2012).
[Crossref]

Costa, M. R.

M. R. Costa, F. Ortega, M. S. Brill, R. Beckervordersandforth, C. Petrone, T. Schroeder, M. Götz, and B. Berninger, “Continuous live imaging of adult neural stem cell division and lineage progression in vitro,” Development 138, 1057–1068 (2011).
[Crossref]

Crozier, K.

D’Ambrosio, M. V.

Z. F. Phillips, M. V. D’Ambrosio, L. Tian, J. J. Rulison, H. S. Patel, N. Sadras, A. V. Gande, N. A. Switz, D. A. Fletcher, and L. Waller, “Multi-contrast imaging and digital refocusing on a mobile microscope with a domed led array,” PLoS ONE 10, e0124938 (2015).
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Supplementary Material (4)

NameDescription
» Visualization 1: MOV (19808 KB)      Large SBP phase video of unstained HeLa cells under-going division over the course of 4 hours at 2 minute intervals.
» Visualization 2: MOV (17410 KB)      Large SBP phase video captured with sub-second acquisition speed (1.25 Hz) for fast dynamics and across long time scales (up to 4.5 hours) for slower evolution for adult rat neural stem cells in vitro.
» Visualization 3: MOV (34744 KB)      Comparisons of phase reconstructions between our source-coded FPM and differential phase contrast for human mammary epithelial cells undergoing division and migration.
» Visualization 4: MOV (9037 KB)      Comparisons of phase reconstructions between our source-coded FPM and differential phase contrast for adult rat neural stem cells.

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Figures (5)

Fig. 1.
Fig. 1.

Source-coded FPM captures large-SBP images in under 1 s. (A) The experimental setup is a microscope with an LED array source and a wide-FOV 4× (0.2 NA) objective. Multiple images are captured with coded illumination in order to reconstruct higher resolution (up to 0.8 NA). (B) Comparison of illumination schemes in terms of space, bandwidth, and acquisition time. Sequential FPM scans through each LED, achieving a large SBP at the cost of speed. Our source-coded FPM implements hybrid patterning to achieve the same SBP with a subsecond acquisition time. (C) The number of images required for source-coded FPM (blue) grows more than 8× slower than that for sequential FPM (red) as the final resolution increases (solid lines, theoretical; points, our LED array).

Fig. 2.
Fig. 2.

Large-SBP reconstructions of quantitative phase and intensity. (A) Phase reconstruction across the full FOV of a 4× objective with 0.7 NA resolution (sample, U2OS). A zoom-in is shown to the right, with comparison with reconstructions of the same sample before and after staining. (B) Our improved FPM algorithm provides better reconstruction of low-frequency phase information. A zoom-in region shows comparisons between phase reconstructions with and without our DPC initialization scheme. (C) To validate our source-coded FPM results, we compare with images captured with a 40× objective having high resolution (0.65 NA) but a small FOV (sample, MCF10A), as well as with sequential FPM. (D) We simulate a phase-contrast image and compare with one captured by a high-resolution objective (0.65 NA, 40×).

Fig. 3.
Fig. 3.

Time-lapse large-SBP phase reconstruction of unstained HeLa cells undergoing division. (A) Sample raw data and Fourier coverage using sequential FPM (173 images), with an acquisition time of 7 s per frame. (B) One frame of the full-FOV phase reconstruction using a 4× objective and achieving 0.8 NA resolution. (C) Several frames of reconstructed video (see Visualization 1) from a zoom-in of one small area of confluent cells in which one cell is dividing into multiple cells. (D) Automated cell segmentation result for the full-FOV phase image, with 3400 cells identified successfully. (E) Calculated dry mass for each of the labeled cells in the zoom-in region over 4 h at 2 min intervals. To the right is a histogram of the background fluctuations in an area with no cells.

Fig. 4.
Fig. 4.

Large-SBP phase video reconstructions for observing multiscale temporal dynamics of in vitro NSCs with a high SBP and an acquisition time of 0.8 s per frame. (A) Our source-coded FPM captures four bright-field images and 17 multiplexed dark-field images. (B) Full-FOV phase reconstruction using a 4× objective and achieving 0.8 NA resolution. (C) Sample frames of reconstructed video (see Visualization 2) for a zoom-in of one small area. Top: successive frames at the maximum frame rate (1.25 Hz). Bottom: sample frames across the longer time lapse (4.5 h at 1 min intervals).

Fig. 5.
Fig. 5.

Motion blur degrades the effective resolution in live dynamic samples. Reconstructed phase of live samples using different capture schemes with the same nominal spatial resolution (0.8 NA) but different acquisition times. As the capture speed increases, more details about subcellular dynamics become visible due to reduced motion blur. Two fast dynamical processes in MCF10A cells, (A) subcellular fiber motion and (B) vesicle transport (Visualization 3), are blurred out when acquisition times are longer than 1 s. Our source-coded FPM achieves subsecond capture, revealing more details, yet not as clearly as DPC, which has the fastest capture time. (C, D) Results for NSCs, which exhibit slower dynamics than the MCF10A cells. Sequential FPM blurs out most subcellular features; however, our source-coded FPM is able to capture details without motion artifacts (Visualization 4).

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