Researchers have developed a deep learning algorithm for removing systematic effects from atomic force microscopy images, enabling more precise profiles of material surfaces. Atomic force microscopy, ...
Morning Overview on MSN
Cornell’s EMSeek uses AI to turn microscopy images into results in 2 to 5 minutes
Cornell University researchers have built an AI system called EMSeek that can analyze an electron microscopy image and ...
Left: wide-field second harmonic generation intensity measurement of a murine muscle slice, where the structure is visible but distorted by out-of-focus light. Right: harmonic optical tomography ...
Integrating Digital Holographic Microscopy with fluorescence techniques enhances live-cell imaging, preserving cellular ...
Researchers have developed a new AI method that produces sharp microscopy images throughout thick biological samples. This video shows how the method, DeAbe, restores highly dynamic time-lapse images ...
In a study published in Science Advances, a team of bioengineering researchers at the University of Illinois Urbana-Champaign developed an algorithm known as adaptive intersection maximization, or AIM ...
Tech Xplore on MSN
Diffusion-based AI model successfully trained in electroplating
Electrochemical deposition, or electroplating, is a common industrial technique that coats materials to improve corrosion ...
A microscope built in the UK is the first in the world to produce 3-D internal pictures of objects. This microscope combines two techniques, X-ray microtomography -- which produces 3-D images from a ...
Atomic force microscopy, or AFM, is a widely used technique that can quantitatively map material surfaces in three dimensions, but its accuracy is limited by the size of the microscope’s probe. A new ...
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