A key step in ultrasound image formation is digital beamforming of signals sampled by several transducer elements placed upon an array. High-resolution digital beamforming introduces the demand for sampling rates significantly higher than the signals' Nyquist rate, which greatly increases the volume of data that must be transmitted from the system's front end. In 3-D ultrasound imaging, 2-D transducer arrays rather than 1-D arrays are used, and more scan lines are needed. This implies that the amount of sampled data is vastly increased with respect to 2-D imaging. In this work, we show that a considerable reduction in data rate can be achieved by applying the ideas of Xampling and frequency domain beamforming (FDBF), leading to a sub-Nyquist sampling rate, which uses only a portion of the bandwidth of the ultrasound signals to reconstruct the image. We extend previous work on FDBF for 2-D ultrasound imaging to accommodate the geometry imposed by volumetric scanning and a 2-D grid of transducer elements. High image quality from low-rate samples is demonstrated by simulation of a phantom image composed of several small reflectors. Our technique is then applied to raw data of a heart ventricle phantom obtained by a commercial 3-D ultrasound system. We show that by performing 3-D beamforming in the frequency domain, sub-Nyquist sampling and low processing rate are achievable, while maintaining adequate image quality.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1109/TUFFC.2016.2535280 | DOI Listing |
We propose a dual-wavelength scheme for a clipping-avoidance photonic analog-to-digital converter (PADC) operating at the sub-Nyquist sampling rate. The scheme utilizes two characteristics, the phase-wrapping feature of a PADC and the wavelength-sensitive feature of a phase modulator, equivalently performing a dual-modulus (DM) modulo operation to avoid clipping. Coupled with an unwrapping algorithm based on the Chinese remainder theorem (CRT), the proposed scheme enables signal reconstruction from the processed signals independent of the sampling rate.
View Article and Find Full Text PDFBiomed Opt Express
November 2024
Department of Electrical Engineering, Columbia University, 500 W 120th Street, New York, NY 10027, USA.
Compressed sensing (CS) is an approach that enables comprehensive imaging by reducing both imaging time and data density, and is a theory that enables undersampling far below the Nyquist sampling rate and guarantees high-accuracy image recovery. Prior efforts in the literature have focused on demonstrations of synthetic undersampling and reconstructions enabled by compressed sensing. In this paper, we demonstrate the first physical, hardware-based sub-Nyquist sampling with a galvanometer-based OCT system with subsequent reconstruction enabled by compressed sensing.
View Article and Find Full Text PDFIEEE Trans Ultrason Ferroelectr Freq Control
August 2024
Conventional medical ultrasound systems utilizing focus-beam imaging generally acquire multichannel echoes at frequencies in tens of megahertz after each transmission, resulting in significant data volumes for digital beamforming. Furthermore, integrating state-of-the-art beamformers with transmission compounding substantially increases the beamforming complexity. Except for upgrading the hardware system for better computing performance, an alternative strategy for accelerating ultrasound data processing is the wavenumber beamforming algorithm, which has not been effectively extended to synthetic focus-beam transmission imaging.
View Article and Find Full Text PDFSensors (Basel)
April 2024
The Department of Space Control and Communications, Space Engineering University, Beijing 102249, China.
Sub-Nyquist synthetic aperture radar (SAR) based on pseudo-random time-space modulation has been proposed to increase the swath width while preserving the azimuthal resolution. Due to the sub-Nyquist sampling, the scene can be recovered by an optimization-based algorithm. However, these methods suffer from some issues, e.
View Article and Find Full Text PDFThis paper presents an electronic skin (e-skin) taxel array readout chip in 0.18μm CMOS technology, achieving the highest reported spatial resolution of 200μm, comparable to human fingertips. A key innovation is the integration on chip of a 12×16 polyvinylidene fluoride (PVDF)-based piezoelectric sensor array with per-taxel signal conditioning frontend and spiking readout combined with local embedded neuromorphic first-order processing through Complex Receptive Fields (CRFs).
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!