A5007001351- Photoacoustic and Ultrasonic Imaging
- Ultrasound Imaging and Elastography
- Ultrasound and Hyperthermia Applications
- Ultrasonics and Acoustic Wave Propagation
- Flow Measurement and Analysis
- Optical measurement and interference techniques
- Image Processing Techniques and Applications
- Indoor and Outdoor Localization Technologies
- Underwater Acoustics Research
- Antenna Design and Optimization
- Microwave Imaging and Scattering Analysis
- Image and Signal Denoising Methods
Stanford University
2022-2024
Promising advances in flexible array technology present new opportunities for wearable ultrasound. However, arrays have non-rigid shapes and thus unknown element positions, posing a major challenge image reconstruction. We introduce robust method estimating the shape of ultrasound from data itself. By implementing delay-and-sum (DAS) beamformer an automatic differentiation framework, we show that phase error between translating subapertures can be used as loss function is backpropagated...
Wavefield imaging reconstructs physical properties from wavefield measurements across an aperture, using modalities like radar, optics, sonar, seismic, and ultrasound imaging. Propagation of a wavefront unknown sources through heterogeneous media causes phase aberrations that degrade the coherence leading to reduced image resolution contrast. Adaptive techniques attempt correct aberration restore improved focus. We propose autofocusing paradigm for correction in by fitting acoustic velocity...
Linear frequency-modulated (chirp) transmits have been used successfully in the past to increase penetration depth of ultrasound signals tissue and improve signal-to-noise ratio (SNR) resulting images. However, beamforming chirp using delay-and-sum (DAS) can be slow on systems without a GPU. We propose scaling algorithm (CSA), originally developed for synthetic aperture radar, as faster alternative DAS CPU that results similar image quality, especially at larger depths. To perform...
To produce high-resolution ultrasound images, synthetic aper-ture acquisitions are used, which contain a large amount of data that is difficult to beamform in real time with traditional methods like delay and sum (DAS). Although frequency do-main beamforming have been adapted ultrasound, the existing adaptations require interpolation. The chirp scaling algorithm (CSA), was originally developed for radar remote sensing applications, avoids interpolation by using Fourier transform shift...
The ability to maintain image uniformity and high resolution over large depths is important for several clinical applications of ultrasound, including deep abdominal imaging in patients with BMI. One way improve quality such cases use retrospective transmit focusing, which involves combining received data from different focused transmits SNR outside focal zone. Retrospective typically accomplished using the delay-and-sum (DAS) beamforming, can be slow on systems without a GPU. As faster...
Abdominal diagnostic ultrasound imaging fails in more than 20% of cases due to the degrading effects body wall. Aberration estimation and correction is crucial, yet challenging, for improving medical diagnostics. To estimate sound speed distribution throughout an imaged area calculating spatially varying beamforming delays that account tissue inhomogeneities, we have developed a neural network approach was trained from simulated liver dataset utilizing anatomically derived human wall maps...
Deep learning has gained tremendous popularity as a tool for ultrasound beamforming and image reconstruction. In previous work, we trained deep neural networks (DNNs) to estimate the echogenicity of medium, improve acoustical electronic signal-to-noise ratio (SNR) in channel data, detect targeted microbubbles nondestructively real-time molecular imaging. Here, present several advancements each application. First, compare speckle- noise-reducing performance DNNs with simple linear Field II...