In the past decade, membraneless assemblies known as biomolecular condensates have
been reported to play key roles in many cellular functions by compartmentalizing specific …

Single-molecule localization microscopy (SMLM) describes a family of powerful imaging
techniques that dramatically improve spatial resolution over standard, diffraction-limited …

Glioblastomas are incurable tumors infiltrating the brain. A subpopulation of glioblastoma
cells forms a functional and therapy-resistant tumor cell network interconnected by tumor …

Generalist methods for cellular segmentation have good out-of-the-box performance on a
variety of image types; however, existing methods struggle for images that are degraded by …

The goal when imaging bioprocesses with optical microscopy is to acquire the most
spatiotemporal information with the least invasiveness. Deep neural networks have …

Light sheet fluorescence microscopy (LSFM) uses a thin sheet of light to excite only
fluorophores within the focal volume. Light sheet microscopes (LSMs) have a true optical …

A main determinant of the spatial resolution of live-cell super-resolution (SR) microscopes is
the maximum photon flux that can be collected. To further increase the effective resolution …

Deep Learning (DL) methods are powerful analytical tools for microscopy and can
outperform conventional image processing pipelines. Despite the enthusiasm and …

Abstract Vision Transformers (ViTs), with the magnificent potential to unravel the information
contained within images, have evolved as one of the most contemporary and dominant …

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 …