Stanford inventors have created a novel, interactive, highly scalable computational approach for representing dynamic brain activity as a network for use in clinical settings.
Stanford researchers have designed and prototyped an inexpensive, compact and easy-to-use smartphone lens mount for the capture of high quality photographs and videos of the eye's front and back structures.
Researchers in the Molecular Imaging Instrumentation Laboratory at Stanford University have developed a PET (positron emission tomography) detector and front end readout assembly that can operate in a high field MRI (magnetic resonance imaging) system.
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 at the Liao and Xing Labs have developed and tested a machine learning algorithm for augmented detection of bladder cancer. Machine learning has the potential to enhance medical decision making in cancer detection and image analysis.
Stanford researchers have developed a method for manufacturing a UV curable epoxy micro lens. Apertures of arbitrary size can be manufactured for micro lenses using this method.
Stanford researchers have developed mutant Renilla luciferase proteins and reporter gene constructs which modify the physical characteristics of the Renilla luciferase protein for use in biological assays.
Stanford researchers have designed a non-invasive, low power ultrasonic neuromodulation device which can target tissue deep in the brain with high spatial-temporal resolution.
Researchers in Prof. Steven Chu's laboratory have developed a fundamentally new method of acoustic imaging to improve resolution of ultrasound diagnostics.
Stanford researchers have developed an exceptionally fast, sensitive, and compact X-ray imaging system for distinguishing liquids and other materials in aviation security applications.
Stanford researchers have proposed a novel, in vivo, real-time epifluorescence imaging method in the second near-infrared region using single-walled carbon nanotubes (SWNTs).
Dr. Manish Saggar at Stanford University has developed a new method to visualize and quantify transitions in brain activity, which may be used as a diagnostic tool for mental illness.
Researchers at Stanford have developed an in vivo drug release monitoring method using magnetic particle imaging (MPI). In vivo drug release monitoring is beneficial to doctors as it provides information to guide drug dosing and helps reduce therapeutic side effects.