Stanford Researchers have developed a method for a high-resolution photon imaging device with high fill factor (the ratio of the area of the active imaging elements vs. the dead area occupied by non-imaging elements).
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.
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).
Mammography is the current first-line imaging technique for early breast cancer detection, however, its diagnostic accuracy is limited in women with dense breast tissue. Ultrasound is often performed as a second line test in women with dense breast tissue.
Stanford researchers have developed a statistical method to map tissue activity distribution and photon attenuation, correcting for attenuation in real time without a transmission scan, using Positron Emission Tomography.
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.
This patented ultrasound imaging system reduces the hardware complexity for coherent array image formation and restoration. This technology is especially useful when there are fewer front-end electronic channels than the number of transducer elements in an array.
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.