Stanford researchers at the Steven Chu Lab have developed and patented a method and apparatus to optimize speckle suppression in ultrasound imaging, usable for diagnostic purposes. This method uses Fourier-transform limited pulses for spectral compounding.
Stanford researchers at the Ferrara Lab have designed an ultra-fast standing device for breast ultrasound which is more comfortable than current designs and has higher resolution.
Stanford researchers have developed a novel approach to ultrasound imaging using the differentiable beamforming pipeline, which optimizes critical imaging parameters, significantly enhancing image quality and diagnostic accuracy in ultrasound imaging.
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 controllable methodology for molecularly targeted ultrasound contrast agent production with pre-formed ligand-phospholipid bioconjugates.
Stanford researchers have developed a next-generation computational algorithm for diagnostic of pulmonary hypertension (PH) that provides an estimate of the tricuspid regurgitation (TR) velocity (Vmax) with increased accuracy and confidence.
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.
Stanford researchers developed a programmable tuning circuit for dynamic, all-electronic tuning of the resonance frequency, sensitivity, and bandwidth of ultrasound transducers.
Ultrasound technology is a safe, high-resolution, and cost-efficient tool for imaging. Other modalities, such as MRI or CT, may require the use of anesthesia. This makes it difficult to image pediatric patients and patients sensitive to anesthesia.
A common hurdle for many drug delivery applications is getting the desired compounds to the targeted cells or receptors. Additional barriers of achieving the therapeutic drug concentration and necessary drug diffusion are also present even after successful targeted delivery.
Stanford researchers at the Airan Lab have developed a new deep learning approach to dramatically reduce the amount of ultrasound data required to produce high quality power Doppler images for functional ultrasound (fUS).
Stanford researchers have developed an algorithm using deep learning architectures to predict cardiac function (ejection fraction) and trace the endocardium of the left ventricle from ultrasound echocardiogram videos.
Stanford researchers have demonstrated the application of pulsed Focused Ultrasound (pFUS), to non-invasively enhance the function and engraftment of pancreatic islets following transplantation.