CGChengfei Guo

Chengfei Guo

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Chengfei Guo has a total of 24 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • High-throughput digital pathology via a handheld, multiplexed, and AI-powered ptychographic whole slide scanner

    by Shaowei Jiang, Chengfei Guo, Pengming Song, Tianbo Wang, Ruihai Wang, Terrance Zhang, Qian Wu, Rishikesh Pandey, Guoan Zheng

    The handheld, do-it-yourself ptychographic whole slide scanner for high-throughput digital pathology applications.


  • Ptychographic sensor for large-scale lensless microbial monitoring with high spatiotemporal resolution

    by Shaowei Jiang, Chengfei Guo, Zichao Bian, Ruihai Wang, Jiakai Zhu, Pengming Song, Patrick Hu, Derek Hu, Zibang Zhang, Kazunori Hoshino, et al.


  • Optofluidic ptychography on a chip

    by Pengming Song, Chengfei Guo, Shaowei Jiang, Tianbo Wang, Patrick Hu, Derek Hu, Zibang Zhang, Bin Feng, Guoan Zheng

    We report the implementation of a fully on-chip, lensless microscopy technique termed optofluidic ptychography. This imaging modality complements the miniaturization provided by microfluidics and allows the integration of ptychographic microscopy into various lab-on-a-chip devices. In our prototype, we place a microfluidic channel on the top surface of a coverslip and coat the bottom surface with a scattering layer. The channel and the coated coverslip substrate are then placed on top of an image sensor for diffraction data acquisition. Similar to the operation of a flow cytometer, the device utilizes microfluidic flow to deliver specimens across the channel. The diffracted light from the flowing objects is modulated by the scattering layer and recorded by the image sensor for ptychographic reconstruction, where high-resolution quantitative complex images are recovered from the diffraction measurements. By using an image sensor with a 1.85 μm pixel size, our device can resolve the 550 nm linewidth on the resolution target. We validate the device by imaging different types of biospecimens, including C. elegans, yeast cells, paramecium, and closterium sp. We also demonstrate a high-resolution ptychographic reconstruction at a video framerate of 30 frames per second. The reported technique can address a wide range of biomedical needs and engenders new ptychographic imaging innovations in a flow cytometer configuration.


  • Super-resolved multispectral lensless microscopy via angle-tilted, wavelength-multiplexed ptychographic modulation

    by Pengming Song, Ruihai Wang, Jiakai Zhu, Tianbo Wang, Zichao Bian, Zibang Zhang, Kazunori Hoshino, Michael Murphy, Shaowei Jiang, Chengfei Guo, et al.

    We report an angle-tilted, wavelength-multiplexed ptychographic modulation approach for multispectral lensless on-chip microscopy. In this approach, we illuminate the specimen with lights at five wavelengths simultaneously. A prism is added at the illumination path for spectral dispersion. Thus, lightwaves at different wavelengths hit the specimen at slightly different incident angles, breaking the ambiguities in mixed-state ptychographic reconstruction. At the detection path, we place a thin diffuser between the specimen and the monochromatic image sensor for encoding the spectral information into 2D intensity measurements. By scanning the sample to different x − y positions, we acquire a sequence of monochromatic images for reconstructing the five complex object profiles at the five wavelengths. An up-sampling procedure is integrated into the recovery process to bypass the resolution limit imposed by the imager pixel size. We demonstrate a half-pitch resolution of 0.55 µm using an image sensor with 1.85 µm pixel size. We also demonstrate quantitative and high-quality multispectral reconstructions of stained tissue sections for digital pathology applications.


  • Wide-field, high-resolution lensless on-chip microscopy via near-field blind ptychographic modulation

    by Shaowei Jiang, Jiakai Zhu, Pengming Song, Chengfei Guo, Zichao Bian, Ruihai Wang, Yikun Huang, Shiyao Wang, He Zhang, Guoan Zheng

    We report a novel lensless on-chip microscopy platform based on near-field blind ptychographic modulation. In this platform, we place a thin diffuser in between the object and the image sensor for light wave modulation. By blindly scanning the unknown diffuser to different x–y positions, we acquire a sequence of modulated intensity images for quantitative object recovery. Different from previous ptychographic implementations, we employ a unit magnification configuration with a Fresnel number of ∼50 000, which is orders of magnitude higher than those of previous ptychographic setups. The unit magnification configuration allows us to have the entire sensor area, 6.4 mm by 4.6 mm, as the imaging field of view. The ultra-high Fresnel number enables us to directly recover the positional shift of the diffuser in the phase retrieval process, addressing the positioning accuracy issue plaguing regular ptychographic experiments. In our implementation, we use a low-cost, DIY scanning stage to perform blind diffuser modulation. Precise mechanical scanning that is critical in conventional ptychography experiments is no longer needed in our setup. We further employ an up-sampling phase retrieval scheme to bypass the resolution limit set by the imager pixel size and demonstrate a half-pitch resolution of 0.78 μm. We validate the imaging performance via in vitro cell cultures, transparent and stained tissue sections, and a thick biological sample. We show that the recovered quantitative phase map can be used to perform effective cell segmentation of a dense yeast culture. We also demonstrate 3D digital refocusing of the thick biological sample based on the recovered wavefront. The reported platform provides a cost-effective and turnkey solution for large field-of-view, high-resolution, and quantitative on-chip microscopy. It is adaptable for a wide range of point-of-care-, global-health-, and telemedicine-related applications.