Self-inspired learning for denoising live-cell super-resolution microscopy
L Qu, S Zhao, Y Huang, X Ye, K Wang, Y Liu, X Liu… - Nature …, 2024 - nature.com
Every collected photon is precious in live-cell super-resolution (SR) microscopy. Here, we
describe a data-efficient, deep learning-based denoising solution to improve diverse SR …
describe a data-efficient, deep learning-based denoising solution to improve diverse SR …
Coordinate-based neural representations for computational adaptive optics in widefield microscopy
Widefield microscopy is widely used for non-invasive imaging of biological structures at
subcellular resolution. When applied to a complex specimen, its image quality is degraded …
subcellular resolution. When applied to a complex specimen, its image quality is degraded …
Pixel-wise programmability enables dynamic high-SNR cameras for high-speed microscopy
High-speed wide-field fluorescence microscopy has the potential to capture biological
processes with exceptional spatiotemporal resolution. However, conventional cameras …
processes with exceptional spatiotemporal resolution. However, conventional cameras …
Deepphysinet: Bridging deep learning and atmospheric physics for accurate and continuous weather modeling
Accurate weather forecasting holds significant importance to human activities. Currently,
there are two paradigms for weather forecasting: Numerical Weather Prediction (NWP) and …
there are two paradigms for weather forecasting: Numerical Weather Prediction (NWP) and …
Deep-prior odes augment fluorescence imaging with chemical sensors
To study biological signalling, great effort goes into designing sensors whose fluorescence
follows the concentration of chemical messengers as closely as possible. However, the …
follows the concentration of chemical messengers as closely as possible. However, the …
From Pixels to Information: Artificial Intelligence in Fluorescence Microscopy
This review explores how artificial intelligence (AI) is transforming fluorescence microscopy,
providing an overview of its fundamental principles and recent advancements. The roles of …
providing an overview of its fundamental principles and recent advancements. The roles of …
Rapid and Noise‐Resilient Mapping of Photogenerated Carrier Lifetime in Halide Perovskite Thin Films
Halide perovskite materials offer significant promise for solar energy and optoelectronics yet
understanding and enhancing their efficiency and stability require addressing lateral …
understanding and enhancing their efficiency and stability require addressing lateral …
Convolutional neural network transformer (CNNT) for fluorescence microscopy image denoising with improved generalization and fast adaptation
A Rehman, A Zhovmer, R Sato, Y Mukouyama… - Scientific Reports, 2024 - nature.com
Deep neural networks can improve the quality of fluorescence microscopy images. Previous
methods, based on Convolutional Neural Networks (CNNs), require time-consuming training …
methods, based on Convolutional Neural Networks (CNNs), require time-consuming training …
TAG‐SPARK: Empowering High‐Speed Volumetric Imaging With Deep Learning and Spatial Redundancy
YT Hsieh, KC Jhan, JC Lee, GJ Huang… - Advanced …, 2024 - Wiley Online Library
Two‐photon high‐speed fluorescence calcium imaging stands as a mainstream technique
in neuroscience for capturing neural activities with high spatiotemporal resolution. However …
in neuroscience for capturing neural activities with high spatiotemporal resolution. However …
DENOISING: Dynamic enhancement and noise overcoming in multimodal neural observations via high-density CMOS-based biosensors
Large-scale multimodal neural recordings on high-density biosensing microelectrode arrays
(HD-MEAs) offer unprecedented insights into the dynamic interactions and connectivity …
(HD-MEAs) offer unprecedented insights into the dynamic interactions and connectivity …