Nonstationary image artifacts frequently arise in MRI from off-resonance and motion. Current methods to correct these nonstationary effects are computationally expensive. Stanford researchers have developed a new deep learning framework to improve image quality in minutes.
Stanford researchers have developed an improved imaging protocol for better visualization of the thalamus. This faster acquisition leads to a better delineation of structures due to the multiple dimensions of information.
Stanford researchers have developed a method which can simultaneously observe two positron emitting isotopes using two distinct molecular probes and a modified PET scanner. This system enables the simultaneous observation of two different molecular processes.
Stanford researchers have prototyped a system to enhance the sensitivity of triple coincidences for multi-isotope PET by adding an extra detector dedicated for the detection of the third prompt gamma in coincidence with the annihilation photons.
A Stanford researcher has developed two advanced approaches for the positron sensitive high-energy photon sensor technology for Positron Emission Tomography (PET).
Current techniques for reconstructing images in positron emission tomography (PET) cannot correctly use events in which at least one photon of a pair has scattered in tissue (also known as scatter coincidence events).
Stanford researchers have patented a novel concept for a position sensitive high-energy photon sensor device for high resolution radiation imaging that can enhance capabilities of Positron Emission Tomography (PET).
Multi-channel coil receivers for magnetic resonance imaging (MRI) accelerate the scan for fast imaging. Acceleration is typically achieved by subsampling the data acquisition and leveraging the localized spatial profiles of each coil element to reconstruct the images.
Researchers in the Khuri-Yakub laboratory have developed patented two dimensional (2D) capacitive micromachined ultrasonic transducer (CMUT) arrays and methods for fabricating them with direct wafer bonding.
Stanford researchers have developed a lanthanide-doped upconverting nanoparticle (UCNP) that emits very photostable and non-blinking light, and is bright enough to delineate tumor boundaries to the naked eye during surgery.
Stanford researchers have developed two related inventions which advance the state-of-the-art of CMUT's (capacitive micromachined ultrasonic transducers).
Stanford researchers at the Dahl Lab have developed a method to reduce artifacts in ultrasound image reconstruction using a trained convolutional neural network (CNN).
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.