Stanford researchers have developed CheXpert which can reduce noise and identify several pathologies on x-rays with very high accuracy via machine learning. CheXpert can read photos of x-rays from a mobile phone and is robust to noise.
Stanford researchers have developed an exceptionally fast, sensitive, and compact X-ray imaging system for distinguishing liquids and other materials in aviation security applications.
This invention, the “Charge Cloud Tracker” is a fast, low-cost, strip geometry x-ray detector that is predicted to provide limiting resolution on the order of 5 microns, with very high x-ray detection efficiency.
Stanford researchers have developed a novel traveling wave accelerating structure which is a critical component of a particle accelerator. It has high shunt impedance similar to that of side-coupled standing-wave accelerating structure, but without its drawbacks.
Stanford researchers have invented a decoder for multiplexed readouts of imaging arrays that optimizes the signal-to-noise ratio (SNR) of the decoded detector pixel signals.
Stanford researchers have developed a system and method to increase sampling in x-ray and CT images by deflecting the focal spot of an x-ray tube. This invention achieves focal spot z-wobble by shaping the rotating anode.
Scatter radiation in an x-ray imaging system including an x-ray source and an x-ray detector is separated by using amplitude modulation to translate the spatial frequency of a detected x-ray beam to a higher frequency and provide separation from low frequency scatter signal.
Researchers in the Ginzton lab at Stanford University have patented an all-dielectric laser-driven microstructure for producing controllable charged particle beam.