Deep learning for cellular image analysis
Recent advances in computer vision and machine learning underpin a collection of
algorithms with an impressive ability to decipher the content of images. These deep learning …
algorithms with an impressive ability to decipher the content of images. These deep learning …
Deep learning in nano-photonics: inverse design and beyond
Deep learning in the context of nano-photonics is mostly discussed in terms of its potential
for inverse design of photonic devices or nano-structures. Many of the recent works on …
for inverse design of photonic devices or nano-structures. Many of the recent works on …
The role of machine learning to boost the bioenergy and biofuels conversion
The development and application of bioenergy and biofuels conversion technology can play
a significant role for the production of renewable and sustainable energy sources in the …
a significant role for the production of renewable and sustainable energy sources in the …
Machine learning for active matter
The availability of large datasets has boosted the application of machine learning in many
fields and is now starting to shape active-matter research as well. Machine learning …
fields and is now starting to shape active-matter research as well. Machine learning …
Avoiding a replication crisis in deep-learning-based bioimage analysis
Deep learning algorithms are powerful tools for analyzing, restoring and transforming
bioimaging data. One promise of deep learning is parameter-free one-click image analysis …
bioimaging data. One promise of deep learning is parameter-free one-click image analysis …
A survey on applications of deep learning in microscopy image analysis
Z Liu, L Jin, J Chen, Q Fang, S Ablameyko, Z Yin… - Computers in biology …, 2021 - Elsevier
Advanced microscopy enables us to acquire quantities of time-lapse images to visualize the
dynamic characteristics of tissues, cells or molecules. Microscopy images typically vary in …
dynamic characteristics of tissues, cells or molecules. Microscopy images typically vary in …
DeepSTORM3D: dense 3D localization microscopy and PSF design by deep learning
An outstanding challenge in single-molecule localization microscopy is the accurate and
precise localization of individual point emitters in three dimensions in densely labeled …
precise localization of individual point emitters in three dimensions in densely labeled …
Quantitative digital microscopy with deep learning
Video microscopy has a long history of providing insight and breakthroughs for a broad
range of disciplines, from physics to biology. Image analysis to extract quantitative …
range of disciplines, from physics to biology. Image analysis to extract quantitative …
Single-shot self-supervised object detection in microscopy
Object detection is a fundamental task in digital microscopy, where machine learning has
made great strides in overcoming the limitations of classical approaches. The training of …
made great strides in overcoming the limitations of classical approaches. The training of …
Current capabilities and future perspectives of FCS: super-resolution microscopy, machine learning, and in vivo applications
J Sankaran, T Wohland - Communications Biology, 2023 - nature.com
Fluorescence correlation spectroscopy (FCS) is a single molecule sensitive tool for the
quantitative measurement of biomolecular dynamics and interactions. Improvements in …
quantitative measurement of biomolecular dynamics and interactions. Improvements in …