Meiqi Li

This paper introduces qHiFi-SIM, a physics-driven self-supervised learning framework for quantitative high-fidelity structured illumination microscopy, achieving excellent intensity linearity and structural fidelity without ground-truth data.

This paper introduces 3D-ADE, a toolkit for adaptive 3D deconvolution and evaluation of volumetric fluorescence microscopy, improving resolution and fidelity through physics-based PSF calibration and deep learning.

This paper introduces DeepUI, a physics-driven framework that reconstructs isotropic 3D fluorescence images from undersampled axial data, achieving high performance even under challenging conditions.

This paper introduces FA-SIM, a super-resolution microscopy technique that quantitatively maps intracellular microenvironment and cytoskeletal dynamics with high accuracy and low phototoxicity.

This study determines the cryo-EM structure of stomatin, revealing its role in organizing functional membrane microdomains and identifying associated proteins involved in cell migration and vesicle trafficking.

This paper introduces a method to remove defocus backgrounds in fluorescence microscopy using dark channels and dual frequency separation, significantly improving image quality.

This paper introduces a 3D orientation mapping microscope that achieves high temporal-spatial resolution for fluorescent dipoles, revealing molecular structure and dynamics in biological systems.

This paper introduces a high-speed 3DSIM system using DMD and electro-optic modulators, achieving improved resolution and imaging speed for various biological specimens.