We present deep-learning-enabled super-resolution across different fluorescence
microscopy modalities. This data-driven approach does not require numerical modeling of the …

The cell membrane is one of the most complicated biological complexes, and long-term fierce
debates regarding the cell membrane persist because of technical hurdles. With the rapid …

Early identification of pathogenic bacteria in food, water, and bodily fluids is very important
and yet challenging, owing to sample complexities and large sample volumes that need to be …

We demonstrate that a deep neural network can significantly improve optical microscopy,
enhancing its spatial resolution over a large field of view and depth of field. After its training, …

The histological analysis of tissue samples, widely used for disease diagnosis, involves
lengthy and laborious tissue preparation. Here, we show that a convolutional neural network …

Atomic force microscopy (AFM) has evolved from the originally morphological imaging
technique to a powerful and multifunctional technique for manipulating and detecting the …

Atomic force microscopy is a powerful and widely used imaging technique that can visualize
single molecules and follow processes at the single-molecule level both in air and in …

As a transmembrane protein, CD47 plays an important role in mediating cell proliferation,
migration, phagocytosis, apoptosis, immune homeostasis, inhibition of NO signal transduction …

We demonstrate that a deep neural network can be trained to virtually refocus a two-dimensional
fluorescence image onto user-defined three-dimensional (3D) surfaces within the …

Mobile phones have facilitated the creation of field-portable, cost-effective imaging and
sensing technologies that approach laboratory-grade instrument performance. However, the …