Hankel Structured Low Rank and Sparse Representation Via L0-Norm Optimization for Compressed Ultrasound Plane Wave Signal Reconstruction
04 Jun 2023-
TL;DR: In this article , a low-rank and joint-sparse model is proposed to reduce the amount of sampled channel data of focused beam imaging by considering all the received data as a 2D matrix.
Abstract: Ultrasound plane wave imaging is widely used in many applications thanks to its capability in reaching high frame rates. However, the amount of data acquisition and storage in a period of time can become a bottleneck in ultrasound system design for thousands frames per second. In our previous study, we proposed a low-rank and joint-sparse model to reduce the amount of sampled channel data of focused beam imaging by considering all the received data as a 2D matrix. However, for a single plane wave transmission, the number of channels is limited and the low-rank property of the received data matrix is no longer achieved. In this study, a L
0 -norm based Hankel structured low-rank and sparse model is proposed to reduce the channel data. An optimization algorithm, based on the alternating direction method of multipliers (ADMM), is proposed to efficiently solve the resulting optimization problem. The performance of the proposed approach was evaluated using the data published in Plane Wave Imaging Challenge in Medical Ultrasound (PICMUS) in 2016. Results on channel and plane wave data show that the proposed method is better adapted to the ultrasound channel signal and can recover the image with fewer samples than the conventional CS method.
TL;DR: The theory of compressive sampling, also known as compressed sensing or CS, is surveyed, a novel sensing/sampling paradigm that goes against the common wisdom in data acquisition.
Abstract: Conventional approaches to sampling signals or images follow Shannon's theorem: the sampling rate must be at least twice the maximum frequency present in the signal (Nyquist rate). In the field of data conversion, standard analog-to-digital converter (ADC) technology implements the usual quantized Shannon representation - the signal is uniformly sampled at or above the Nyquist rate. This article surveys the theory of compressive sampling, also known as compressed sensing or CS, a novel sensing/sampling paradigm that goes against the common wisdom in data acquisition. CS theory asserts that one can recover certain signals and images from far fewer samples or measurements than traditional methods use.
TL;DR: It is proposed to improve the beamforming process by using a coherent recombination of compounded plane-wave transmissions to recover high-quality echographic images without degrading the high frame rate capabilities.
Abstract: The emergence of ultrafast frame rates in ultrasonic imaging has been recently made possible by the development of new imaging modalities such as transient elastography. Data acquisition rates reaching more than thousands of images per second enable the real-time visualization of shear mechanical waves propagating in biological tissues, which convey information about local viscoelastic properties of tissues. The first proposed approach for reaching such ultrafast frame rates consists of transmitting plane waves into the medium. However, because the beamforming process is then restricted to the receive mode, the echographic images obtained in the ultrafast mode suffer from a low quality in terms of resolution and contrast and affect the robustness of the transient elastography mode. It is here proposed to improve the beamforming process by using a coherent recombination of compounded plane-wave transmissions to recover high-quality echographic images without degrading the high frame rate capabilities. A theoretical model is derived for the comparison between the proposed method and the conventional B-mode imaging in terms of contrast, signal-to-noise ratio, and resolution. Our model predicts that a significantly smaller number of insonifications, 10 times lower, is sufficient to reach an image quality comparable to conventional B-mode. Theoretical predictions are confirmed by in vitro experiments performed in tissue-mimicking phantoms. Such results raise the appeal of coherent compounds for use with standard imaging modes such as B-mode or color flow. Moreover, in the context of transient elastography, ultrafast frame rates can be preserved while increasing the image quality compared with flat insonifications. Improvements on the transient elastography mode are presented and discussed.
TL;DR: In this article, a linear array transducer was used to estimate the 2D vector velocity of the blood using 2-D cross-correlation, which was obtained with a frame-rate of 100 Hz where 40 speckle images were used for each vector velocity image.
Abstract: Conventional ultrasound methods for acquiring color images of blood velocity are limited by a relatively low frame-rate and are restricted to give velocity estimates along the ultrasound beam direction only. To circumvent these limitations, the method presented in this paper uses 3 techniques: 1) The ultrasound is not focused during the transmissions of the ultrasound signals; 2) A 13 -bit Barker code is transmitted simultaneously from each transducer element; and 3) The 2-D vector velocity of the blood is estimated using 2-D cross-correlation. A parameter study was performed using the Field II program, and performance of the method was investigated when a virtual blood vessel was scanned by a linear array transducer. An improved parameter set for the method was identified from the parameter study, and a flow rig measurement was performed using the same improved setup as in the simulations. Finally, the common carotid artery of a healthy male was scanned with a scan sequence that satisfies the limits set by the Food and Drug Administration. Vector velocity images were obtained with a frame-rate of 100 Hz where 40 speckle images are used for each vector velocity image. It was found that the blood flow approximately followed the vessel wall, and that maximum velocity was approximately 1 m/s, which is a normal value for a healthy person. To further evaluate the method, the test person was scanned with magnetic resonance (MR) angiography. The volume flow derived from the MR scanning was compared with that from the ultrasound scanning. A deviation of 9% between the 2 volume flow estimates was found.
••01 Sep 2016
TL;DR: PICMUS, the Plane-Wave Imaging Challenge in Medical Ultrasound aims to provide tools to compensate for the lack of transmit focusing in plane-Wave imaging, and its motivation, implementation, and metrics.
Abstract: Plane-Wave imaging enables very high frame rates, up to several thousand frames per second. Unfortunately the lack of transmit focusing leads to reduced image quality, both in terms of resolution and contrast. Recently, numerous beamforming techniques have been proposed to compensate for this effect, but comparing the different methods is difficult due to the lack of appropriate tools. PICMUS, the Plane-Wave Imaging Challenge in Medical Ultrasound aims to provide these tools. This paper describes the PICMUS challenge, its motivation, implementation, and metrics.
TL;DR: A relatively simple design that replaces each analog delay line with a tapped, digital shift register (DSR) and a digital phase shift operation adjusted for midband will provide the desired performance, provided that the sampling rate of the signal at the input to the DSR is 4 to 10 times the bandwidth.
Abstract: The effects on array gain and sidelobe level of a practical digital beamforming (DBF) processor under the wideband conditions typical of ultrasound is discussed. It is concluded that a relatively simple design that replaces each analog delay line with a tapped, digital shift register (DSR) and a digital phase shift operation adjusted for midband will provide the desired performance, provided that the sampling rate of the signal at the input to the DSR is 4 to 10 times the bandwidth. More realistically, when nonidealized passbands are taken into account and the typical condition whereby the transducer frequency is about twice the bandwidth is considered, the rule of thumb for the sampling rate is that it must be 4 to 10 times the transducer frequency. >