A decade of unprecedented progress in artificial intelligence (AI) has demonstrated the
potential for many fields—including medicine—to benefit from the insights that AI techniques …

Artificial intelligence tasks across numerous applications require accelerators for fast and
low-power execution. Optical computing systems may be able to meet these domain-specific …

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 …

Image-based profiling is a maturing strategy by which the rich information present in
biological images is reduced to a multidimensional profile, a collection of extracted image …

The use of artificial intelligence, and the deep-learning subtype in particular, has been
enabled by the use of labeled big data, along with markedly enhanced computing power …

The proliferation of microscopy methods for live-cell imaging offers many new possibilities
for users but can also be challenging to navigate. The prevailing challenge in live-cell …

Label‐free super‐resolution (LFSR) imaging relies on light‐scattering processes in
nanoscale objects without a need for fluorescent (FL) staining required in super‐resolved FL …

Protein subcellular localization is tightly controlled and intimately linked to protein function in
health and disease. Capturing the spatial proteome—that is, the localizations of proteins and …

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 …

Deep learning is becoming an increasingly important tool for image reconstruction in
fluorescence microscopy. We review state-of-the-art applications such as image restoration …