Deep Coherence Learning: An Unsupervised Deep Beamformer for High Quality Single Plane Wave Imaging in Medical Ultrasound

Plane wave imaging (PWI) in medical ultrasound is becoming an important reconstruction method with high frame rates and new clinical applications. Recently, single PWI based on deep learning (DL) has been studied to overcome lowered frame rates of traditional PWI with multiple PW transmissions. However, due to the lack of appropriate ground truth images, DL-based PWI still remains challenging for performance improvements. To address this issue, in this paper, we propose a new unsupervised learning approach, i.e., deep coherence learning (DCL)-based DL beamformer (DL-DCL), for high-quality single PWI. In DL-DCL, the DL network is trained to predict highly correlated signals with a unique loss function from a set of PW data, and the trained DL model encourages high-quality PWI from low-quality single PW data. In addition, the DL-DCL framework based on complex baseband signals enables a universal beamformer. To assess the performance of DL-DCL, simulation, phantom and in vivo studies were conducted with public datasets, and it was compared with traditional beamformers (i.e., DAS with 75-PWs and DMAS with 1-PW) and other DL-based methods (i.e., supervised learning approach with 1-PW and generative adversarial network (GAN) with 1-PW). From the experiments, the proposed DL-DCL showed comparable results with DMAS with 1-PW and DAS with 75-PWs in spatial resolution, and it outperformed all comparison methods in contrast resolution. These results demonstrated that the proposed unsupervised learning approach can address the inherent limitations of traditional PWIs based on DL, and it also showed great potential in clinical settings with minimal artifacts

A New Fast Logarithm Algorithm Using Advanced Exponent Bit Extraction for Software-Based Ultrasound Imaging Systems

Ultrasound B-mode imaging provides anatomical images of the body with a high resolution and frame rate. Recently, to improve its flexibility, most ultrasound signal and image processing modules in modern ultrasound B-mode imaging systems have been implemented in software. In a software-based B-mode imaging system, an efficient processing technique for calculating a logarithm instruction is required to support its high computational burden. In this paper, we present a new method to efficiently implement a logarithm operation based on exponent bit extraction. In the proposed method, the exponent bit field is first extracted and then some algebraic operations are applied to improve its precision. To evaluate the performance of the proposed method, the peak signal-to-noise ratio (PSNR) and the execution time were measured. The proposed efficient logarithm operation method substantially reduced the execution time, i.e., eight times, compared to direct computation while providing a PSNR of over 50 dB. These results indicate that the proposed efficient logarithm computation method can be used for lowering the computational burden in software-based ultrasound B-mode ultrasound imaging systems while improving or maintaining the image quality

Vein visualization using a smart phone with multispectral wiener estimation for point-of-care applications

Effective vein visualization is clinically important for various point-of-care applications, such as needle insertion. It can be achieved by utilizing ultrasound imaging or by applying infrared laser excitation and monitoring its absorption. However, while these approaches can be used for vein visualization, they are not suitable for point-of-care applications because of their cost, time, and accessibility. In this paper, a new vein visualization method based on multispectral Wiener estimation is proposed and its real-time implementation on a smart phone is presented. In the proposed method, a conventional RGB camera on a commercial smart phone (i.e., Galaxy Note 2, Samsung Electronics Inc., Suwon, Korea) is used to acquire reflectance information from veins. Wiener estimation is then applied to extract the multispectral information from the veins. To evaluate the performance of the proposed method, an experiment was conducted using a color calibration chart (ColorChecker Classic, X-rite, Grand Rapids, MI, USA) and an average root-mean-square error of 12.0% was obtained. In addition, an in vivo subcutaneous vein imaging experiment was performed to explore the clinical performance of the smart phone-based Wiener estimation. From the in vivo experiment, the veins at various sites were successfully localized using the reconstructed multispectral images and these results were confirmed by ultrasound B-mode and color Doppler images. These results indicate that the presented multispectral Wiener estimation method can be used for visualizing veins using a commercial smart phone for point-of-care applications (e.g., vein puncture guidance)

A Computationally Efficient Mean Sound Speed Estimation Method Based on an Evaluation of Focusing Quality for Medical Ultrasound Imaging

Generally, ultrasound receive beamformers calculate the focusing time delays of fixed sound speeds in human tissue (e.g., 1540 m/s). However, phase distortions occur due to variations of sound speeds in soft tissues, resulting in degradation of image quality. Thus, an optimal estimation of sound speed is required in order to improve image quality. Implementation of real-time sound speed estimation is challenging due to high computational and hardware complexities. In this paper, an optimal sound speed estimation method with a low-cost hardware resource is presented. In the proposed method, the optimal mean sound speed is determined by measuring the amplitude variance of pre-beamformed radio-frequency (RF) data. The proposed method was evaluated with phantom and in vivo experiments, and implemented on Virtex-4 with Xilinx ISE 12.4 using VHDL. Experiment results indicate that the proposed method could estimate the mean optimal sound speed and enhance spatial resolution with a negligible increase in the hardware resource usage

Coded tissue harmonic imaging with nonlinear chirp signals

Coded tissue harmonic imaging with pulse inversion (CTHI-PI) based on a linear chirp signal can improve the signal-to-noise ratio with minimizing the peak range sidelobe level (PRSL), which is the main advantage over CTHI with bandpass filtering (CTHI-BF). However, the CTHI-PI technique could suffer from motion artifacts due to decreasing frame rate caused by two firings of opposite phase signals for each scanline. In this paper, a new CTHI method based on a nonlinear chirp signal (CTHI-NC) is presented, which can improve the separation of fundamental and harmonic components without sacrificing frame rate. The nonlinear chirp signal is designed to minimize the PRSL value by optimizing its frequency sweep rate and time duration. The performance of the CTHI-NC method was evaluated by measuring the PRSL and mainlobe width after compression. From the in vitro experiments, the CTHI-NC provided the PRSL of -40.6 dB and the mainlobe width of 2.1 mu s for the transmit quadratic nonlinear chirp signal with the center frequency of 2.1 MHz, the fractional bandwidth at -6 dB of 0.6 and the time duration of 15 mu s. These results indicate that the proposed method could be used for improving frame rates in CTHI while providing comparable image quality to CTHI-PI. (C) 2010 Elsevier B.V. All rights reserved

Real-time monitoring of HIFU treatment using pulse inversion

Ultrasound (US) imaging is widely used for the real-time guidance of high-intensity focused ultrasound (HIFU) treatment at a relatively low cost. However, ultrasound image guided HIFU (USgHIFU) is limited in the real-time monitoring of HIFU treatment due to the large amplitude HIFU signals received by the US imaging transducer. The amplitude of the HIFU scattered signal is generally much higher than the amplitude of the pulse-echo signal received by the imaging transducer. This creates an interference pattern obscuring the image of the tissue. As such, it is difficult to monitor lesion location. This paper proposes a real-time monitoring method to be performed concurrently with the HIFU insonation, but without HIFU interference, which allows for the improvement of treatment accuracy and safety in USgHIFU. The proposed method utilizes the physical properties of pulse inversion which is capable of removing the fundamental and odd harmonic components of the HIFU interference. Therefore, it is possible to secure the desired spectral bandwidth used to construct US images for HIFU treatment monitoring. The performance of the proposed method was evaluated through experiments with both a bovine serum albumin phantom and a chicken breast. The results demonstrated that the proposed method is capable of providing interference-free US images, thus successfully allowing for US imaging during HIFU treatment

Air-Coupled Ultrasound Sealing Integrity Inspection Using Leaky Lamb Waves in a Simplified Model of a Lithium-Ion Pouch Battery: Feasibility Study

Inspecting the sealing integrity of lead tabs is an important means of ensuring the reliability and safety of pouch-type lithium-ion (Li-ion) batteries with a thin multi-layered aluminum (Al) laminated film. This paper presents a new air-coupled ultrasonic non-destructive testing (NDT) inspection method based on leaky Lamb wave transmission; and reception for evaluating the sealing integrity between the lead tab and the Al pouch film. The proposed method uses the critical incidence angle between the air and the layer with the fastest Lamb wave velocity to maximize the signal-to-noise ratio in the through-transmission mode. To determine the critical incidence angle, phantom experiments with two test pieces (i.e., an Al tab and an Al tab sealed with an Al pouch film) are conducted. In addition, 2D scans are performed at various incidence angles for an inhouse pouch-type Li-ion battery with a 1-mm-wide foreign material inserted as a defect. At the critical incidence angle (i.e., 22°), the proposed air-coupled ultrasonic NDT method in through-transmission mode successfully identifies the shape and location of the defect through c-scan image reconstruction. These preliminary results indicate that the proposed air-coupled ultrasonic NDT method with leaky Lamb waves can be used to inspect the sealing integrity of Li-ion pouch batteries in dry test conditions

Design and Implementation of a New Wireless Carotid Neckband Doppler System with Wearable Ultrasound Sensors: Preliminary Results

Noninvasive monitoring of blood flow in the carotid artery is important for evaluating not only cerebrovascular but also cardiovascular diseases. In this paper, a wireless neckband ultrasound Doppler system, in which two 2.5-MHz ultrasonic sensors are utilized for acquiring Doppler signals from both carotid arteries, is presented for continuously evaluating blood flow dynamics. In the developed wireless neckband Doppler system, the acquired Doppler signals are quantized by 14-bit analog-to-digital-converters running at 40 MHz, and pre-processing operations (i.e., demodulation and clutter filtering) are performed in an embedded field programmable gate array chip. Then, these data are transferred to an external smartphone (i.e., Galaxy S7, Samsung Electronics Co., Suwon, Korea) via Bluetooth 2.0. Post-processing (i.e., Fourier transform and image processing) is performed using an embedded application processor in the smartphone. The developed carotid neckband Doppler system was evaluated with phantom and in vivo studies. In a phantom study, the neckband Doppler system showed comparable results with a commercial ultrasound machine in terms of peak systolic velocity and resistive index, i.e., 131.49 ± 3.97 and 0.75 ± 0.02 vs. 131.89 ± 2.06 and 0.74 ± 0.02, respectively. In addition, in the in vivo study, the neckband Doppler system successfully demonstrated its capability to continuously evaluate hemodynamics in both common carotid arteries. These results indicate that the developed wireless neckband Doppler system can be used for continuous monitoring of blood flow dynamics in the common carotid arteries in point-of-care settings