Stanford researchers have created the first large-scale dataset of aerial videos from multiple classes of targets interacting in complex outdoor spaces.
Stanford researchers have developed a new machine learning method for extracting gait parameters, such as cadence, step length, peak knee flexion, and Gait Deviation Index (GDI), from a single video.
Stanford researchers have developed a novel phantom which can integrate quality assurance (QA) procedures for radiofrequency tracking system, surface mapping system, Winston-Lutz test, the imaging system isocenter test and laser verification.
Stanford researchers have developed a novel and efficient method for generating real-time 3D volumetric computed tomography (CT) images with 2D single or few-view projections, instead of several hundreds of projections as required in existing CT imaging system.
Prof. Alison Marsden and her colleagues have developed a computational framework that uses personalized anatomical information to identify patients that have a high risk for saphenous vein graft (SVG) failure after coronary artery bypass graft (CABG).
Stanford researchers have invented a C-Aperture Nano-Tip which provides a new way to further enhance the optical resolution down to smaller than 15 nm.
When examining one or higher dimensional data, researchers frequently aim to identify individual subsets (clusters) of objects within the dataset. With high-dimensional data (>3 dimensions), the data become progressively more sparsly distributed in space.
Stanford researchers have recently patented a hybrid LED-LCD screen suitable for applications ranging from large televisions to small mobile displays and capable of significantly reducing power consumption to as little as 1/20th that of conventional design
Engineers in Prof. Khuri-Yakub's laboratory have developed ultrasonic methods for non-invasive flow meters to accurately measure flow rate, pressure, velocity and other parameters of gas or liquid traveling through a pipe.
Engineers in Prof. Khuri-Yakub's laboratory have developed ultrasonic methods for non-invasive flow meters to accurately measure flow rate, pressure, velocity profile and other parameters of gas or liquid traveling through a pipe.
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 designed a system to enable x-ray visualization of the tracheobronchial tree to aid the physician in guiding endoscopic tools in the pulmonary tract.
Disease indication - HIV infection, specifically reversal of viral latency alone or in combination with other latency reversal agents to improve reservoir targeting.