Stanford researchers have developed a method for identifying the foveal center in the eye for high resolution retinal mapping in adaptive optics devices using artificial intelligence.
Stanford inventors have developed an early-stage screening method to diagnose abdominal aortic aneurysms (AAA). AAA is a common cardiovascular disease with high prevalence in European men 65 years and above.
Stanford researchers have developed a new method of imaging cholesteatoma, an expanding and destructive lesion of the middle ear and mastoid, based on its chemical composition.
Stanford scientists have invented a new PET-nanophotonic metamaterial scintillator that consists of tunable scintillating alkaline-earth rare-earth fluoride nanoparticles (MLnF) for low-dose, high-resolution PET imaging.
Researchers at Stanford have developed an innovation that will enhance the depth of the imaging capabilities for optical coherence tomography (OCT) imaging.
Active manipulation of light beams is required for a range of emerging optical technologies, including sensing, optical computing, virtual/augmented reality, dynamic holography, and computational imaging.
Researchers in Prof. Karl Deisseroth's laboratory have patented a revolutionary technique that can be utilized to map neural circuits in the whole brain.
Researchers at Stanford University have established a deep learning segmentation algorithm for non-contrast CT images to aid clinicians in decision making and improve the speed of symptom to treatment in acute ischemic stroke
Stanford scientists developed a novel strategy that uses resting-state functional connectivity magnetic resonance imaging (rs-fMRI) to determine whether a person will respond to treatment for depression.
Stanford researchers have developed a compact, scalable electronic readout that can multiplex 24 or more fast outputs of each 6x4 SiPM array to only 1 timing channel per detector layer unit.
Stanford inventors have created a novel, interactive, highly scalable computational approach for representing dynamic brain activity as a network for use in clinical settings.
Researchers at Stanford have developed a methodology for deep learning-based image reconstruction by incorporating the physics or geometry priors of the imaging system with deep neural networks.
Stanford researchers have developed a new controllable methodology for molecularly targeted ultrasound contrast agent production with pre-formed ligand-phospholipid bioconjugates.
Stanford researchers from the Khuri-Yakub group have designed an improved, high spatial resolution ultrasonic neuromodulation device that implements chip waveform instead of continuous wave PIRF.