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 …

Live-cell imaging experiments have opened an exciting window into the behavior of living
systems. While these experiments can produce rich data, the computational analysis of these …

A principal challenge in the analysis of tissue imaging data is cell segmentation—the task of
identifying the precise boundary of every cell in an image. To address this problem we …

Deep learning is transforming the ability of life scientists to extract information from images.
While these techniques have superior accuracy in comparison to conventional approaches …

Plasma membrane disruption can trigger a host of cellular activities. One commonly observed
type of disruption is pore formation. Molecular dynamic (MD) simulations of simplified lipid …

Deep learning is transforming the analysis of biological images, but applying these models
to large datasets remains challenging. Here we describe the DeepCell Kiosk, cloud-native …

A bipolar (BP) nanosecond electric pulse (nsEP) exposure generates reduced calcium influx
compared to a unipolar (UP) nsEP. This attenuated physiological response from a BP nsEP …

Nanosecond electric pulse (nsEP) exposure generates an array of physiological effects.
The extent of these effects is impacted by whether the nsEP is a unipolar (UP) or bipolar (BP) …

The requirement of center asymmetry for the creation of second harmonic generation (SHG)
signals makes it an attractive technique for visualizing changes in interfacial layers such as …

The Game-Engine-Assisted Research platform for Scientific computing (GEARS) is a visualization
framework developed at the Materials Genome Innovation for Computational Software …