Microsoft5d
Convolutional neural network transformer (CNNT) for fluorescence microscopy image denoising with improved generalization and fast adaptation
outperforming models trained using only CNNs such as 3D-RCAN and Noise2Fast. We show three examples of efficacy of this approach in wide-field, two-photon, and confocal fluorescence microscopy.
Quantum properties in atom-thick semiconductors offer new way to detect electrical signals in cells
For decades, scientists have relied on electrodes and dyes to track the electrical activity of living cells. Now, engineers ...
Nature2d
Milestones in light microscopy
A supplement contextualizes key advances in light microscopy over 400 years, while the Tara expedition sets sail to explore oceanic ecosystems at the microscopic level. Microscopes were also in ...
The Field Museum6d
Exhibitions & 3D Movies
Explore cultures present and past, find the latest scientific discoveries, and travel the world right here in Chicago.