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Ultrasound/Photoacoustic Sensing and Imaging in Biomedical Applications

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".

Deadline for manuscript submissions: 25 April 2024 | Viewed by 10672

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Prof. Dr. Shyh-Hau Wang

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Guest Editor

Department of Computer Science and Information Engineering & Institute of Medical Informatics, National Cheng Kung University, Tainan 70101, Taiwan
Interests: ultrasound signal and imaging technologies; machine/deep learning classification; signal and image processing; medical and healthcare informatics

Special Issue Information

Dear Colleagues,

Medical imaging plays an essential role in the clinical diagnosis and prognosis of internal tissue and organs of the human body. Several medical imaging modalities are not only able to noninvasively image the interior of a body for clinical analysis and medical intervention, but also provide quantitative information about the properties and function of certain organs or tissues. Among them, ultrasound and photoacoustic imaging techniques have several advantages and the potential to provide better structural and functional information about biological tissues efficiently, cost effectively, and safely. Alongside the growth of AI, computational power and sensors techniques, new imaging technologies and novel analysis techniques in ultrasound and photoacoustic imaging are continuously being explored and developed. The results of these cutting-edge developments certainly provide numerous insights and opportunities for improving the diagnostics, procedures and even basic research investigations. The objective of this Special Issue is to demonstrate advances in sensing, imaging and image analysis of photoacoustic and ultrasound imaging techniques for biomedical applications.

For this Special Issue, the topics of interest include, but are not limited to:

Novel ultrasound imaging techniques/modalities;
Photoacoustic imaging techniques/modalities;
Transducers/sensors for ultrasound imaging/photoacoustic imaging system;
Ultrasound parametric/functional imaging
Machine/deep learning of ultrasound images for characterizing tissues.

Prof. Dr. Shyh-Hau Wang
Guest Editor

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Published Papers (6 papers)

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Research

21 pages, 7059 KiB

Open AccessArticle

Transcranial Ultrasonic Focusing by a Phased Array Based on Micro-CT Images

by Yuxin Yin, Shouguo Yan, Juan Huang and Bixing Zhang

Sensors 2023, 23(24), 9702; https://doi.org/10.3390/s23249702 - 08 Dec 2023

Viewed by 856

Abstract

In this paper, we utilize micro-computed tomography (micro-CT) to obtain micro-CT images with a resolution of 60 μm and establish a micro-CT model based on the k-wave toolbox, which can visualize the microstructures in trabecular bone, including pores and bone layers. The transcranial ultrasound phased array focusing field characteristics in the micro-CT model are investigated. The ultrasonic waves are multiply scattered in skull and time delays calculations from the transducer to the focusing point are difficult. For this reason, we adopt the pulse compression method and the linear frequency modulation Barker code to compute the time delay and implement phased array focusing in the micro-CT model. It is shown by the simulation results that ultrasonic loss is mainly caused by scattering from the microstructures of the trabecular bone. The ratio of main and side lobes of the cross-correlation calculation is improved by 5.53 dB using the pulse compression method. The focusing quality and the calculation accuracy of time delay are improved. Meanwhile, the beamwidth at the focal point and the sound pressure amplitude decrease with the increase in the signal frequency. Focusing at different depths indicates that the beamwidth broadens with the increase in the focusing depth, and beam deflection focusing maintains good consistency in the focusing effect at a distance of 9 mm from the focal point. This indicates that the phased-array method has good focusing results and focus tunability in deep cranial brain. In addition, the sound pressure at the focal point can be increased by 8.2% through amplitude regulation, thereby enhancing focusing efficiency. The preliminary experiment verification is conducted with an ex vivo skull. It is shown by the experimental results that the phased array focusing method using pulse compression to calculate the time delay can significantly improve the sound field focusing effect and is a very effective transcranial ultrasound focusing method. Full article

(This article belongs to the Special Issue Ultrasound/Photoacoustic Sensing and Imaging in Biomedical Applications)

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11 pages, 2367 KiB

Open AccessArticle

Dynamic Speed of Sound Adaptive Transmission–Reflection Ultrasound Computed Tomography

by Xiangwei Lin, Hongji Shi, Zhenyu Fu, Haoming Lin, Siping Chen, Xin Chen and Mian Chen

Sensors 2023, 23(7), 3701; https://doi.org/10.3390/s23073701 - 03 Apr 2023

Viewed by 1576

Abstract

Ultrasound computed tomography (USCT) can visualize a target with multiple imaging contrasts, which were demonstrated individually previously. Here, to improve the imaging quality, the dynamic speed of sound (SoS) map derived from the transmission USCT will be adapted for the correction of the acoustic speed variation in the reflection USCT. The variable SoS map was firstly restored via the optimized simultaneous algebraic reconstruction technique with the time of flights selected from the transmitted ultrasonic signals. Then, the multi-stencils fast marching method was used to calculate the delay time from each element to the grids in the imaging field of view. Finally, the delay time in conventional constant-speed-assumed delay and sum (DAS) beamforming would be replaced by the practical computed delay time to achieve higher delay accuracy in the reflection USCT. The results from the numerical, phantom, and in vivo experiments show that our approach enables multi-modality imaging, accurate target localization, and precise boundary detection with the full-view fast imaging performance. The proposed method and its implementation are of great value for accurate, fast, and multi-modality USCT imaging, particularly suitable for highly acoustic heterogeneous medium. Full article

(This article belongs to the Special Issue Ultrasound/Photoacoustic Sensing and Imaging in Biomedical Applications)

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13 pages, 6267 KiB

Open AccessArticle

Ultrasonic High-Resolution Imaging and Acoustic Tweezers Using Ultrahigh Frequency Transducer: Integrative Single-Cell Analysis

by Hayong Jung, K. Kirk Shung and Hae Gyun Lim

Sensors 2023, 23(4), 1916; https://doi.org/10.3390/s23041916 - 08 Feb 2023

Cited by 2 | Viewed by 1951

Abstract

Ultrasound imaging is a highly valuable tool in imaging human tissues due to its non-invasive and easily accessible nature. Despite advances in the field of ultrasound research, conventional transducers with frequencies lower than 20 MHz face limitations in resolution for cellular applications. To address this challenge, we employed ultrahigh frequency (UHF) transducers and demonstrated their potential applications in the field of biomedical engineering, specifically for cell imaging and acoustic tweezers. The lateral resolution achieved with a 110 MHz UHF transducer was 20 μm, and 6.5 μm with a 410 MHz transducer, which is capable of imaging single cells. The results of our experiments demonstrated the successful imaging of a single PC-3 cell and a 15 μm bead using an acoustic scanning microscope equipped with UHF transducers. Additionally, the dual-mode multifunctional UHF transducer was used to trap and manipulate single cells and beads, highlighting its potential for single-cell studies in areas such as cell deformability and mechanotransduction. Full article

(This article belongs to the Special Issue Ultrasound/Photoacoustic Sensing and Imaging in Biomedical Applications)

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23 pages, 7602 KiB

Open AccessArticle

A Tiled Ultrasound Matrix Transducer for Volumetric Imaging of the Carotid Artery

by Djalma Simões dos Santos, Fabian Fool, Moein Mozaffarzadeh, Maysam Shabanimotlagh, Emile Noothout, Taehoon Kim, Nuriel Rozsa, Hendrik J. Vos, Johan G. Bosch, Michiel A. P. Pertijs, Martin D. Verweij and Nico de Jong

Sensors 2022, 22(24), 9799; https://doi.org/10.3390/s22249799 - 14 Dec 2022

Cited by 1 | Viewed by 2388

Abstract

High frame rate three-dimensional (3D) ultrasound imaging would offer excellent possibilities for the accurate assessment of carotid artery diseases. This calls for a matrix transducer with a large aperture and a vast number of elements. Such a matrix transducer should be interfaced with an application-specific integrated circuit (ASIC) for channel reduction. However, the fabrication of such a transducer integrated with one very large ASIC is very challenging and expensive. In this study, we develop a prototype matrix transducer mounted on top of multiple identical ASICs in a tiled configuration. The matrix was designed to have 7680 piezoelectric elements with a pitch of 300 μm × 150 μm integrated with an array of 8 × 1 tiled ASICs. The performance of the prototype is characterized by a series of measurements. The transducer exhibits a uniform behavior with the majority of the elements working within the −6 dB sensitivity range. In transmit, the individual elements show a center frequency of 7.5 MHz, a −6 dB bandwidth of 45%, and a transmit efficiency of 30 Pa/V at 200 mm. In receive, the dynamic range is 81 dB, and the minimum detectable pressure is 60 Pa per element. To demonstrate the imaging capabilities, we acquired 3D images using a commercial wire phantom. Full article

(This article belongs to the Special Issue Ultrasound/Photoacoustic Sensing and Imaging in Biomedical Applications)

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21 pages, 6548 KiB

Open AccessArticle

Two-Dimensional Wavenumber Analysis Implemented in Ultrasonic Vector Doppler Method with Focused Transmit Beams

by Hideyuki Hasegawa, Masaaki Omura, Ryo Nagaoka and Kozue Saito

Sensors 2022, 22(24), 9787; https://doi.org/10.3390/s22249787 - 13 Dec 2022

Cited by 1 | Viewed by 1311

Abstract

The multi-angle Doppler method was introduced for the estimation of velocity vectors by measuring axial velocities from multiple directions. We have recently reported that the autocorrelation-based velocity vector estimation could be ameliorated significantly by estimating the wavenumbers in two dimensions. Since two-dimensional wavenumber estimation requires a snapshot of an ultrasonic field, the method was first implemented in plane wave imaging. Although plane wave imaging is predominantly useful for examining blood flows at an extremely high temporal resolution, it was reported that the contrast in a B-mode image obtained with a few plane wave emissions was lower than that obtained with focused beams. In this study, the two-dimensional wavenumber analysis was first implemented in a framework with focused transmit beams. The simulations showed that the proposed method achieved an accuracy in velocity estimation comparable to that of the method with plane wave imaging. Furthermore, the performances of the methods implemented in focused beam and plane wave imaging were compared by measuring human common carotid arteries in vivo. Image contrasts were analyzed in normal and clutter-filtered B-mode images. The method with focused beam imaging achieved a better contrast in normal B-mode imaging, and similar velocity magnitudes and angles were obtained by both the methods with focused beam and plane wave imaging. In contrast, the method with plane wave imaging gave a better contrast in a clutter-filtered B-mode image and smaller variances in velocity magnitudes than those with focused beams. Full article

(This article belongs to the Special Issue Ultrasound/Photoacoustic Sensing and Imaging in Biomedical Applications)

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18 pages, 6480 KiB

Open AccessArticle

Ultrasound Ultrafast Power Doppler Imaging with High Signal-to-Noise Ratio by Temporal Multiply-and-Sum (TMAS) Autocorrelation

by Che-Chou Shen and Feng-Ting Guo

Sensors 2022, 22(21), 8349; https://doi.org/10.3390/s22218349 - 31 Oct 2022

Cited by 2 | Viewed by 1869

Abstract

Coherent plane wave compounding (CPWC) reconstructs transmit focusing by coherently summing several low-resolution plane-wave (PW) images from different transmit angles to improve its image resolution and quality. The high frame rate of CPWC imaging enables a much larger number of Doppler ensembles such that the Doppler estimation of blood flow becomes more reliable. Due to the unfocused PW transmission, however, one major limitation of the Doppler estimation in CPWC imaging is the relatively low signal-to-noise ratio (SNR). Conventionally, the Doppler power is estimated by a zero-lag autocorrelation which reduces the noise variance, but not the noise level. A higher-lag autocorrelation method such as the first-lag (R(1)) power Doppler image has been developed to take advantage of the signal coherence in the temporal direction for suppressing uncorrelated random noises. In this paper, we propose a novel Temporal Multiply-and-Sum (TMAS) power Doppler detection method to further improve the noise suppression of the higher-lag method by modulating the signal coherence among the temporal correlation pairs in the higher-lag autocorrelation with a tunable pt value. Unlike the adaptive beamforming methods which demand for either receive–channel–domain or transmit–domain processing to exploit the spatial coherence of the blood flow signal, the proposed TMAS power Doppler can share the routine beamforming architecture with CPWC imaging. The simulated results show that when it is compared to the original R(1) counterpart, the TMAS power Doppler image with the pt value of 2.5 significantly improves the SNR by 8 dB for the cross-view flow velocity within the Nyquist rate. The TMAS power Doppler, however, suffers from the signal decorrelation of the blood flow, and thus, it relies on not only the pt value and the flow velocity, but also the flow direction relative to the geometry of acoustic beam. The experimental results in the flow phantom and in vivo dataset also agree with the simulations. Full article

(This article belongs to the Special Issue Ultrasound/Photoacoustic Sensing and Imaging in Biomedical Applications)

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