A5038744675- Advanced Fluorescence Microscopy Techniques
- Cell Image Analysis Techniques
- Optical Coherence Tomography Applications
- Advanced Electron Microscopy Techniques and Applications
- Image Processing Techniques and Applications
- Photoacoustic and Ultrasonic Imaging
- Spectroscopy Techniques in Biomedical and Chemical Research
- Immunotherapy and Immune Responses
- Digital Holography and Microscopy
- Photoreceptor and optogenetics research
- Near-Field Optical Microscopy
- Carbon Nanotubes in Composites
- Extracellular vesicles in disease
- Additive Manufacturing and 3D Printing Technologies
- Electron Spin Resonance Studies
- Planarian Biology and Electrostimulation
- Advanced Neuroimaging Techniques and Applications
- Cellular Mechanics and Interactions
- Material Properties and Applications
- Cellular transport and secretion
- Advanced biosensing and bioanalysis techniques
- Biochemical effects in animals
- Single-cell and spatial transcriptomics
- Calcium signaling and nucleotide metabolism
- Microtubule and mitosis dynamics
Zhejiang University
2016-2025
Hangzhou Normal University
2024
State Key Laboratory of Modern Optical Instruments
2021-2023
Alibaba Group (China)
2021-2022
First Affiliated Hospital Zhejiang University
2022
Zhejiang University of Technology
2021-2022
University of North Carolina at Chapel Hill
1998-2020
Abstract Structured illumination microscopy (SIM) surpasses the optical diffraction limit and offers a two-fold enhancement in resolution over limited microscopy. However, it requires both intense multiple acquisitions to produce single high-resolution image. Using deep learning augment SIM, we obtain five-fold reduction number of raw images required for super-resolution generate under extreme low light conditions (at least 100× fewer photons). We validate performance neural networks on...
Imaging and tracking of near-surface three-dimensional volumetric nanoscale dynamic processes live cells remains a challenging problem. In this paper, we propose multi-color live-cell near-surface-volume super-resolution microscopy method that combines total internal reflection fluorescence structured illumination with multi-angle evanescent light illumination. We demonstrate our approach interference is perfectly adapted to studying subcellular dynamics mitochondria microtubule...
Live-cell imaging of multiple subcellular structures is essential for understanding dynamics. However, the conventional multi-color sequential fluorescence microscopy suffers from significant delays and limited number structure separate labeling, resulting in substantial limitations real-time live-cell research applications. Here, we present Adaptive Explainable Multi-Structure Network (AEMS-Net), a deep-learning framework that enables simultaneous prediction two single image. The model...
Measuring three-dimensional nanoscale cellular structures is challenging, especially when the structure dynamic. Owing to informative total internal reflection fluorescence (TIRF) imaging under varied illumination angles, multi-angle (MA) TIRF has been examined offer a axial and subsecond temporal resolution. However, conventional MA-TIRF still performs badly in lateral resolution fails characterize depth image densely distributed regions. Here, we emphasize super-resolution MA-TIRF,...
High-performance biosensors play a crucial role in elucidating the intricate spatiotemporal regulatory roles and dynamics of membrane phospholipids. However, enhancing sensitivity imaging performance remains significant challenge. Here, optogenetic-based strategies are presented to optimize phospholipid biosensors. These involves presequestering unbound cell nucleus regulating their cytosolic levels with blue light minimize background signal interference detection, particularly under...
Epithelial-mesenchymal transition (EMT) is one of the most important mechanisms in initiation and promotion cancer cell metastasis. The phosphoinositide 3-kinase (PI3K) signaling pathway has been demonstrated to be involved TGF-β induced EMT, but complicated network makes it challenging dissect role PI3K on regulation EMT process. Here, we applied optogenetic controlled module (named 'Opto-PI3K'), which based CRY2 N-terminal CIB1 (CIBN), rapidly reversibly control endogenous activity cells...
Droplet digital PCR (ddPCR) is a technique for absolute quantification of nucleic acid molecules and widely used in biomedical research clinical diagnosis. ddPCR partitions the reaction solution containing target into large number independent microdroplets amplification performs quantitative analysis by calculating proportion positive droplets principle Poisson distribution. Accurate recognition images great importance to guarantee accuracy analysis. However, hand-designed operators are...
In the structured illumination microscopy (SIM) family, interferometric implementations using traditional physical gratings or advanced liquid crystal on silicon spatial light modulators are popular but have disadvantages of expensive and limited speed. A promising alternative a digital micromirror device (DMD) has improved situation for its lower cost higher speed, furthermore, it contributed to proposal simple compact projection DMD-SIM. However, DMD-SIM method is accused erroneously...
Abstract Using deep learning to augment structured illumination microscopy (SIM), we obtained a fivefold reduction in the number of raw images required for super-resolution SIM, and generated under extreme low light conditions (100X fewer photons). We validated performance neural networks on different cellular structures achieved multi-color, live-cell imaging with greatly reduced photobleaching.
Abstract With the development of super‐resolution fluorescence microscopy, complex dynamic processes in living cells can be observed and recorded with unprecedented temporal spatial resolution. Single particle tracking (SPT) is most important step to explore relationship between spatio‐temporal dynamics subcellular molecules their functions. Although previous studies have developed SPT algorithms quantitatively analyze cell, traditional methods poor performance when dealing intersecting...
Fluorescence microscopy has become an essential tool for biologists, to visualize the dynamics of intracellular structures with specific labeling. Quantitatively measuring moving objects inside cell is pivotal understanding underlying regulatory mechanism. Protein-containing vesicles are involved in various biological processes such as material transportation, organelle interaction, and hormonal regulation, whose dynamic characteristics significant disease diagnosis drug screening. Although...
Abstract Fluorescence microscopy is a powerful tool for life sciences, which employs fluorescent tags to label and observe cellular structures their dynamics. However, due the spectral overlap between different dyes, limited number of can be separately labeled imaged live cell applications. Here we propose novel double-structure network (DBSN) that consists multiple connected models, extract six subcellular from three images with only two separate labels. DBSN combines intensity-balance...
DNA-based point accumulation in nanoscale topography (DNA-PAINT) is a well-established technique for single-molecule localization microscopy (SMLM), enabling resolution of up to few nanometers. Traditionally, DNA-PAINT involves the utilization tens thousands fluorescent images generate single super-resolution image. This process can be time-consuming, which makes it unfeasible many researchers. Here, we propose simplified labeling method and deep learning-enabled fast imaging strategy...
As a supplement to optical super-resolution microscopy techniques, computational methods have demonstrated remarkable results in alleviating the spatiotemporal imaging trade-off. However, they commonly suffer from low structural fidelity and universality. Therefore, we herein propose deep-physics-informed sparsity framework designed holistically synergize strengths of physical models (image blurring processes), prior knowledge (continuity constraints), back-end optimization algorithm...
The application of computational methods for enhancement the resolution fluorescence microscopy images beyond diffraction limit has emerged in recent years. Among them, super-resolution radial fluctuations (SRRF) and mean-shift (MSSR) are two widely used representatives. However, these often unsatisfactory when dealing with low-quality images, which prone to artifacts as well structure discontinuities. Here, we propose an effective method named morphological filtering polynomial fitting...
Vignetting constitutes a prevalent optical degradation that significantly compromises the quality of biomedical microscopic imaging. However, robust and efficient vignetting correction methodology in multi-channel images remains absent at present. In this paper, we take advantage prior knowledge about homogeneity radial attenuation property to develop self-supervised deep learning algorithm achieves complex removal color images. Our proposed method, lookup table (VCLUT), is trainable on both...