Seung Ah Lee's Imaging Intelligence Laboratory at Seoul National University develops Fourier ptychographic microscopes (FPM) for wide-field, high-resolution quantitative phase imaging: a smartphone FPM (K. C. Lee et al., ACS Photonics 2021), FPM with an OLED display as the light source (K. Lee et al., Opt. Lasers Eng. 2024), single-shot FPM (H. Yoon et al., Appl. Phys. Lett. 2025) and polarization-resolved FPM (H. Chae et al., Laser Photonics Rev. 2026), also used for virtual staining (H. Chae et al., APL Photonics 2024).
A conventional microscope trades field of view for resolution, and unstained cells give little contrast. Fourier ptychography (FP) illuminates the sample from many angles and combines the low-resolution images computationally into a wide-field, high-resolution image with quantitative phase. The illumination comes from an LED array or a display screen, and the images are recorded through an inexpensive low-magnification objective. We have built smartphone, single-shot and polarization-resolved FP microscopes.
7 projects
A smartphone has a camera, a programmable display and a processor. We combined them into a stand-alone Fourier ptychographic microscope (FPM). A compact 3D-printed optics module guides light from the phone's own screen through the sample and into its built-in camera, so lighting up individual spots on the display becomes a programmable, angle-scanning illumination source.
Live-cell imaging usually trades field of view for resolution and often relies on fluorescent labels that can perturb the cells. We built a miniaturized Fourier ptychographic microscope small enough to operate inside a standard CO₂ cell-culture incubator, using a low-magnification 4× objective, a machine-vision camera and an inexpensive LED matrix.
FP is usually illuminated by an LED array, whose millimeter-scale LEDs must sit far from the sample to approximate plane waves. An OLED display instead provides millions of micrometer-sized emitters that can be switched on in any pattern. We studied how to use a high-resolution display screen, placed just beneath the slide, as the illumination source.
Standard FP needs many heavily overlapping images with good signal, which slows acquisition and limits low-cost hardware such as phone-based microscopes. When measurements are sparse or noisy, the inverse problem becomes ill-posed and conventional algorithms produce artifacts.
FP's need for many sequential images makes it too slow for moving samples. We encode several illumination angles into a single exposure: linear polarizers at four orientations tag different groups of LEDs, and a polarization camera, whose pixels separate the four polarization channels, records them all at once.
Many biological structures, from plant cell walls to starch and crystals, are birefringent: they change the polarization of light in ways ordinary images miss. Measuring this usually requires rotating optics or specialized polarization sensors.
Before the lab existed, Prof. Lee's PhD work at Caltech (in Changhuei Yang's group) asked how small and inexpensive a microscope could be. In chip-scale microscopy the sample sits directly on a CMOS image sensor and casts a shadow onto its pixels; sequences of slightly shifted shadow images are then combined by pixel super-resolution to beat the pixel-size limit.
Computational Microscopy
Seung Ah Lee's laboratory develops virtual staining for digital pathology: neural networks convert the quantitative phase of unstained tissue slides, measured by FPM, into images of stained slides (H. Chae et al., APL Photonics 2024; K. C. Lee et al., J. Phys. Photonics 2026).
Pathologists read tissue through chemical stains such as hematoxylin and eosin (H&E). Staining is slow, consumes tissue and reagents, varies from lab to lab, and fades over the years. Unstained tissue is nearly transparent, but it still delays light by an amount set by its local density and thickness. Our Fourier ptychographic microscopes measure this optical phase quantitatively across whole slides, and deep neural networks learn to translate it into the colors of a stained slide. We use this to restore faded archival slides digitally, to co-design illumination and networks so that a slide region is scanned in seconds, and to explore stains beyond H&E, working with pathologists at Severance Hospital.
3 projects
Hematoxylin and eosin stains fade over time, so archived slides that may be needed again for diagnosis or research slowly lose their information. Physical re-staining is laborious and can damage the tissue, and digital color normalization fails once the stain is nearly gone.
Two factors limit virtual staining in clinical workflows: collecting paired stained and unstained training images is costly, and capturing hundreds of FP images per field is slow. We addressed both with a co-designed illumination and network system. An illumination-optimization layer, trained end to end with the network, learns which combinations of the microscope's 193 LEDs carry the most useful information.
Supervised virtual staining depends on pixel-matched image pairs, which are hard to obtain for every tissue type and stain. We are developing unsupervised approaches that learn from unpaired collections of label-free phase images and existing whole-slide images of stained tissue.
23 publications
Kang, Y.G., Chae, H., & Lee, S.A.
Advanced Imaging, 3(3), 033001 (2026) doi:10.3788/AI.2026.30001
Pupil Plane Multiplexing for Vectorial Fourier Ptychography
Chae, H., Lee, K., Kang, Y.G., Yoon, H., Lee, K.C., & Lee, S.A.
Laser & Photonics Reviews, 20(9), e02183 (2026) doi:10.1002/lpor.202502183
Lee, K.C., Chae, H., Kim, J., Kreiss, L., Kim, H., Kang, Y.G., Zhou, K.C., Chaware, A., Kim, K., Xu, S., Kang, S., Bang, G., Cho, N.H., Hwang, D., Horstmeyer, R., & Lee, S.A.
Journal of Physics: Photonics, 8(1), 015025 (2026) doi:10.1088/2515-7647/ae270f
Single-shot Fourier ptychography using polarization-encoded illumination
Yoon, H., Chae, H., Lee, K.C., Lee, K., & Lee, S.A.
Applied Physics Letters, 126(12), 123702 (2025) doi:10.1063/5.0248101
Restoring H&E stain in faded slides via phase-to-color virtual staining in near-infrared
Chae, H., Kim, J., Jeon, J., Lee, K., Lee, K.C., Choi, J.U., Kang, S., Choi, S., Bang, G., Lee, J.H., Park, E., Cho, N.H., & Lee, S.A.
APL Photonics, 9(10), 106112 (2024) doi:10.1063/5.0226277
Anisotropic regularization for sparsely sampled and noise-robust Fourier ptychography
Lee, K.C., Chae, H., Xu, S., Lee, K., Horstmeyer, R., Lee, S.A., & Hong, B.W.
Optics Express, 32(14), 25343–25361 (2024) doi:10.1364/OE.529023
High-resolution display screen as programmable illumination for Fourier ptychography
Lee, K., Lee, K.C., Jung, J., Chae, H., & Lee, S.A.
Optics and Lasers in Engineering, 177, 108121 (2024) doi:10.1016/j.optlaseng.2024.108121
Computational 3D topographic microscopy from terabytes of data per sample
Zhou, K.C., Harfouche, M., Zheng, M., Jönsson, J., Lee, K.C., Kim, K., Appel, R., Reamey, P., Doman, T., Saliu, V., Horstmeyer, G., Lee, S.A., & Horstmeyer, R.
Journal of Big Data, 11(1), 62 (2024) doi:10.1186/s40537-024-00901-0
Tensorial tomographic Fourier ptychography with applications to muscle tissue imaging
Xu, S., Yang, X., Ritter, P., Dai, X., Lee, K.C., Kreiss, L., Zhou, K.C., Kim, K., Chaware, A., Neff, J., Glass, C., Lee, S.A., Friedrich, O., & Horstmeyer, R.
Advanced Photonics, 6(2), 026004 (2024) doi:10.1117/1.AP.6.2.026004
Digital staining in optical microscopy using deep learning - a review
Kreiss, L., Jiang, S., Li, X., Xu, S., Zhou, K.C., Lee, K.C., Mühlberg, A., Kim, K., Chaware, A., Ando, M., Barisoni, L., Lee, S.A., Zheng, G., Lafata, K.J., Friedrich, O., & Horstmeyer, R.
PhotoniX, 4, 34 (2023) doi:10.1186/s43074-023-00113-4
Noniterative sub-pixel shifting super-resolution lensless digital holography
Lee, H., Kim, J., Kim, J., Jeon, P., Lee, S.A., & Kim, D.
Optics Express, 29(19), 29996–30006 (2021) doi:10.1364/OE.433719
A Smartphone-Based Fourier Ptychographic Microscope Using the Display Screen for Illumination
Lee, K.C., Lee, K., Jung, J., Lee, S.H., Kim, D., & Lee, S.A.
ACS Photonics, 8(5), 1307–1315 (2021) doi:10.1021/acsphotonics.1c00350
Yoo, H., Lee, H., Rhee, W.J., Moon, G., Lee, C., Lee, S.A., Shin, J.S., & Kim, D.
Advanced Optical Materials, 9(15), 2100211 (2021) doi:10.1002/adom.202100211
Surface Plasmon Localization-Based Super-resolved Raman Microscopy
Lee, H., Kang, K., Mochizuki, K., Lee, C., Toh, K.A., Lee, S.A., Fujita, K., & Kim, D.
Nano Letters, 20(12), 8951–8958 (2020) doi:10.1021/acs.nanolett.0c04219
LudusScope: accessible interactive smartphone microscopy for life-science education
Kim, H., Gerber, L.C., Chiu, D., Lee, S.A., Cira, N.J., Xia, S.Y., & Riedel-Kruse, I.H.
PLOS ONE, 11(10), e0162602 (2016) doi:10.1371/journal.pone.0162602 Before IIL
A smartphone-based chip-scale microscope using ambient illumination
Lee, S.A., & Yang, C.
Lab on a Chip, 14(16), 3056–3063 (2014) doi:10.1039/C4LC00523F Before IIL
Imaging and identification of waterborne parasites using a chip-scale microscope
Lee, S.A., Erath, J., Zheng, G., Ou, X., Willems, P., Eichinger, D., Rodriguez, A., & Yang, C.
PLOS ONE, 9(2), e89712 (2014) doi:10.1371/journal.pone.0089712 Before IIL
Jung, J.H., Han, C., Lee, S.A., Kim, J., & Yang, C.
Lab on a Chip, 14(19), 3781–3789 (2014) doi:10.1039/C4LC00790E Before IIL
Lee, S.A., Ou, X., Lee, J.E., & Yang, C.
Optics Letters, 38(11), 1817–1819 (2013) doi:10.1364/OL.38.001817 Before IIL
On-chip continuous monitoring of motile microorganisms on an ePetri platform
Lee, S.A., Zheng, G., Mukherjee, N., & Yang, C.
Lab on a Chip, 12(13), 2385–2390 (2012) doi:10.1039/C2LC40090A Before IIL
Lee, S.A., Leitao, R., Zheng, G., Yang, S., Rodriguez, A., & Yang, C.
PLOS ONE, 6(10), e26127 (2011) doi:10.1371/journal.pone.0026127 Before IIL
Zheng, G., Lee, S.A., Antebi, Y., Elowitz, M.B., & Yang, C.
Proceedings of the National Academy of Sciences, 108(41), 16889–16894 (2011) doi:10.1073/pnas.1110681108 Before IIL
Sub-pixel resolving optofluidic microscope for on-chip cell imaging
Zheng, G.*, Lee, S.A.*, Yang, S.*, & Yang, C.
Lab on a Chip, 10(22), 3125–3129 (2010) doi:10.1039/C0LC00213E Before IIL