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

Deadline for manuscript submissions: closed (15 June 2022) | Viewed by 21668

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Special Issue Editor

Prof. Dr. Jae Youn Hwang

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Guest Editor

Daegu Gyeongbuk Institute of Science & Technology, Daegu, Korea
Interests: ultrasonic imaging system; multimodal platforms based on ultrasonic technology; mobile ultrasonic system; wearable ultrasonic sensing system; sensing cell or tissue properties such as molecular, mechanical, and chemical properties

Special Issue Information

For the last few decades, the ultrasound and its relevant multimodal system have been widely utilized as a promising technology in biology and medicine. Currently, ultrasound sensing and imaging systems have become one of the key methods for measuring cell and tissue properties, such as molecular, mechanical, and chemical properties. Recently, the development of various ultrasound sensing and imaging systems has been further explored to meet a broad range of applications.

This Special Issue aims to bring together recent studies on new ultrasound imaging and sensing systems, ultrasound-based multimodal systems, mobile ultrasound systems, ultrasound transducers, and their applications in medicine and biology.

Papers addressing a wide range of ultrasound sensing and imaging innovations are sought, including, but not limited to, recent research and developments in the following areas:

Ultrasound imaging;
Wearable and mobile ultrasonic sensors;
Ultrasonic biosensors;
Ultrasounds in cell sensing;
Multimodal sensing and imaging systems based on ultrasound and optical technology;
Ultrasound-based elastography for the measurement of mechanical properties of cells and tissues;
Other associated devices and applications.

Both review articles and original research papers associated with ultrasonic systems, relevant multimodal systems, ultrasonic sensors/transducers, and their applications in biology and medicine are solicited. There is a particular interest in papers concerning applications of high-frequency ultrasound elastography, multimodal imaging systems for analysis of cells and tissues, and wearable/mobile ultrasonic sensors.

Prof. Dr. JaeYoun Hwang
Guest Editor

Manuscript Submission Information

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Keywords

ultrasound imaging;
multimodal imaging;
high-frequency ultrasound;
wearable ultrasonic systems;
cell/tissue elastography;
mobile ultrasound systems

Published Papers (7 papers)

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15 pages, 3938 KiB

Open AccessArticle

Super-Resolution Ultrasound Imaging Scheme Based on a Symmetric Series Convolutional Neural Network

by Lakpa Dorje Tamang and Byung-Wook Kim

Sensors 2022, 22(8), 3076; https://0-doi-org.brum.beds.ac.uk/10.3390/s22083076 - 16 Apr 2022

Cited by 2 | Viewed by 2613

Abstract

In this paper, we propose a symmetric series convolutional neural network (SS-CNN), which is a novel deep convolutional neural network (DCNN)-based super-resolution (SR) technique for ultrasound medical imaging. The proposed model comprises two parts: a feature extraction network (FEN) and an up-sampling layer. In the FEN, the low-resolution (LR) counterpart of the ultrasound image passes through a symmetric series of two different DCNNs. The low-level feature maps obtained from the subsequent layers of both DCNNs are concatenated in a feed forward manner, aiding in robust feature extraction to ensure high reconstruction quality. Subsequently, the final concatenated features serve as an input map to the latter 2D convolutional layers, where the textural information of the input image is connected via skip connections. The second part of the proposed model is a sub-pixel convolutional (SPC) layer, which up-samples the output of the FEN by multiplying it with a multi-dimensional kernel followed by a periodic shuffling operation to reconstruct a high-quality SR ultrasound image. We validate the performance of the SS-CNN with publicly available ultrasound image datasets. Experimental results show that the proposed model achieves a high-quality reconstruction of the ultrasound image over the conventional methods in terms of peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM), while providing compelling SR reconstruction time. Full article

(This article belongs to the Special Issue Ultrasonic Systems for Biomedical Sensing)

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16 pages, 1677 KiB

Open AccessArticle

Ex Vivo Evaluation of Mechanical Anisotropic Tissues with High-Frequency Ultrasound Shear Wave Elastography

by Seungyeop Lee, Lucy Youngmin Eun, Jae Youn Hwang and Yongsoon Eun

Sensors 2022, 22(3), 978; https://0-doi-org.brum.beds.ac.uk/10.3390/s22030978 - 27 Jan 2022

Cited by 2 | Viewed by 1779

Abstract

The use of imaging devices to assess directional mechanics of tissues is highly desirable. This is because the directional mechanics depend on fiber orientation, and altered directional mechanics are closely related to the pathological status of tissues. However, measuring directional mechanics in tissues with high-stiffness is challenging due to the difficulty of generating localized displacement in these tissues using acoustic radiation force, a general method for generating displacement in ultrasound-based elastography. In addition, common ultrasound probes do not provide rotational function, which makes the measurement of directional mechanics inaccurate and unreliable. Therefore, we developed a high-frequency ultrasound mechanical wave elastography system that can accommodate a wide range of tissue stiffness and is also equipped with a motorized rotation stage for precise imaging of directional mechanics. A mechanical shaker was applied to the elastography system to measure tissues with high-stiffness. Phantom and ex vivo experiments were performed. In the phantom experiments, the lateral and axial resolution of the system were determined to be 144

μ

m and 168

μ

m, respectively. In the ex vivo experiments, we used swine heart and cartilage, both of which are considered stiff. The elastography system allows us to acquire the directional mechanics with high angular resolution in the heart and cartilage. The results demonstrate that the developed elastography system is capable of imaging a wide range of tissues and has high angular resolution. Therefore, this system might be useful for the diagnostics of mechanically anisotropic tissues via ex vivo tests. Full article

(This article belongs to the Special Issue Ultrasonic Systems for Biomedical Sensing)

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19 pages, 26553 KiB

Open AccessArticle

Imbalanced Loss-Integrated Deep-Learning-Based Ultrasound Image Analysis for Diagnosis of Rotator-Cuff Tear

by Kyungsu Lee, Jun Young Kim, Moon Hwan Lee, Chang-Hyuk Choi and Jae Youn Hwang

Sensors 2021, 21(6), 2214; https://0-doi-org.brum.beds.ac.uk/10.3390/s21062214 - 22 Mar 2021

Cited by 16 | Viewed by 3150

Abstract

A rotator cuff tear (RCT) is an injury in adults that causes difficulty in moving, weakness, and pain. Only limited diagnostic tools such as magnetic resonance imaging (MRI) and ultrasound Imaging (UI) systems can be utilized for an RCT diagnosis. Although UI offers comparable performance at a lower cost to other diagnostic instruments such as MRI, speckle noise can occur the degradation of the image resolution. Conventional vision-based algorithms exhibit inferior performance for the segmentation of diseased regions in UI. In order to achieve a better segmentation for diseased regions in UI, deep-learning-based diagnostic algorithms have been developed. However, it has not yet reached an acceptable level of performance for application in orthopedic surgeries. In this study, we developed a novel end-to-end fully convolutional neural network, denoted as Segmentation Model Adopting a pRe-trained Classification Architecture (SMART-CA), with a novel integrated on positive loss function (IPLF) to accurately diagnose the locations of RCT during an orthopedic examination using UI. Using the pre-trained network, SMART-CA can extract remarkably distinct features that cannot be extracted with a normal encoder. Therefore, it can improve the accuracy of segmentation. In addition, unlike other conventional loss functions, which are not suited for the optimization of deep learning models with an imbalanced dataset such as the RCT dataset, IPLF can efficiently optimize the SMART-CA. Experimental results have shown that SMART-CA offers an improved precision, recall, and dice coefficient of 0.604% (+38.4%), 0.942% (+14.0%) and 0.736% (+38.6%) respectively. The RCT segmentation from a normal ultrasound image offers the improved precision, recall, and dice coefficient of 0.337% (+22.5%), 0.860% (+15.8%) and 0.484% (+28.5%), respectively, in the RCT segmentation from an ultrasound image with severe speckle noise. The experimental results demonstrated the IPLF outperforms other conventional loss functions, and the proposed SMART-CA optimized with the IPLF showed better performance than other state-of-the-art networks for the RCT segmentation with high robustness to speckle noise. Full article

(This article belongs to the Special Issue Ultrasonic Systems for Biomedical Sensing)

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14 pages, 2902 KiB

Open AccessArticle

FRET-Based Ca²⁺ Biosensor Single Cell Imaging Interrogated by High-Frequency Ultrasound

by Sangpil Yoon, Yijia Pan, Kirk Shung and Yingxiao Wang

Sensors 2020, 20(17), 4998; https://0-doi-org.brum.beds.ac.uk/10.3390/s20174998 - 03 Sep 2020

Cited by 7 | Viewed by 4345

Abstract

Fluorescence resonance energy transfer (FRET)-based biosensors have advanced live cell imaging by dynamically visualizing molecular events with high temporal resolution. FRET-based biosensors with spectrally distinct fluorophore pairs provide clear contrast between cells during dual FRET live cell imaging. Here, we have developed a new FRET-based Ca²⁺ biosensor using EGFP and FusionRed fluorophores (FRET-GFPRed). Using different filter settings, the developed biosensor can be differentiated from a typical FRET-based Ca²⁺ biosensor with ECFP and YPet (YC3.6 FRET Ca²⁺ biosensor, FRET-CFPYPet). A high-frequency ultrasound (HFU) with a carrier frequency of 150 MHz can target a subcellular region due to its tight focus smaller than 10 µm. Therefore, HFU offers a new single cell stimulations approach for FRET live cell imaging with precise spatial resolution and repeated stimulation for longitudinal studies. Furthermore, the single cell level intracellular delivery of a desired FRET-based biosensor into target cells using HFU enables us to perform dual FRET imaging of a cell pair. We show that a cell pair is defined by sequential intracellular delivery of the developed FRET-GFPRed and FRET-CFPYPet into two target cells using HFU. We demonstrate that a FRET-GFPRed exhibits consistent 10–15% FRET response under typical ionomycin stimulation as well as under a new stimulation strategy with HFU. Full article

(This article belongs to the Special Issue Ultrasonic Systems for Biomedical Sensing)

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14 pages, 7976 KiB

Open AccessArticle

Interleaved Array Transducer with Polarization Inversion Technique to Implement Ultrasound Tissue Harmonic Imaging

by Chan Yuk Park, Jin Ho Sung, Eun Young Jeong, Hee Su Lee and Jong Seob Jeong

Sensors 2020, 20(14), 3915; https://0-doi-org.brum.beds.ac.uk/10.3390/s20143915 - 14 Jul 2020

Cited by 2 | Viewed by 2775

Abstract

In ultrasound tissue harmonic imaging (THI), it is preferred that the bandwidth of the array transducer covers at least the fundamental frequency f₀ for transmission and the second harmonic frequency 2f₀ for reception. However, it is challenging to develop an array transducer with a broad bandwidth due to the single resonance characteristics of piezoelectric materials. In this study, we present an improved interleaved array transducer suitable for THI and a dedicated transducer fabrication scheme. The proposed array transducer has a novel structure in which conventional elements exhibiting f₀ resonant frequency and polarization-inverted elements exhibiting 2f₀ resonant frequency are alternately located, and the thicknesses of all piezoelectric elements are identical. The performance of the proposed method was demonstrated by finite element analysis (FEA) simulations and experiments using a fabricated prototype array transducer. Using the proposed technique, f₀ and 2f₀ frequency ultrasounds can be efficiently transmitted and received, respectively, resulting in a 90% broad bandwidth feature of the transducer. Thus, the proposed technique can be one of the potential ways to implement high resolution THI. Full article

(This article belongs to the Special Issue Ultrasonic Systems for Biomedical Sensing)

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14 pages, 2782 KiB

Open AccessArticle

Fusion iENA Scholar Study: Sensor-Navigated I-124-PET/US Fusion Imaging versus Conventional Diagnostics for Retrospective Functional Assessment of Thyroid Nodules by Medical Students

by Martin Freesmeyer, Thomas Winkens, Luis Weissenrieder, Christian Kühnel, Falk Gühne, Simone Schenke, Robert Drescher and Philipp Seifert

Sensors 2020, 20(12), 3409; https://0-doi-org.brum.beds.ac.uk/10.3390/s20123409 - 17 Jun 2020

Cited by 9 | Viewed by 2104

Abstract

In conventional thyroid diagnostics, the topographical correlation between thyroid nodules (TN) depicted on ultrasound (US) in axial or sagittal orientation and coronally displayed scintigraphy images can be challenging. Sensor-navigated I-124-PET/US fusion imaging has been introduced as a problem-solving tool for ambiguous cases. The purpose of this study was to investigate the results of multiple unexperienced medical students (MS) versus multiple nuclear medicine physicians (MD) regarding the overvalue of I-124-PET/US in comparison to conventional diagnostics (CD) for the functional assessment of TN. Methods: Out of clinical routine, cases with ambiguous findings on CD were selected for I-124-PET/US fusion imaging. Sixty-eight digital patient case files (PCF) of 34 patients (CDonly and CD+PET/US PCF) comprising 66 TN were provided to be retrospectively evaluated by 70 MD and 70 MS, respectively. A total of 2174 ratings (32.9 per TN) were carried out: 555 ratings (8.4 per TN) for CDonly and 532 ratings (8.1 per TN) for CD+PET/US by each MD and MS. Results: Functional assessment revealed 8.5%/11.7% (n.s.) (16.4%/25.8% (p = 0.0002)), 41.8%/28.5% (p < 0.0001) (23.9%/17.9% (p = 0.0193)), 36.0%/30.5% (n.s.) (57.3%/53.9% (n.s.)), and 13.7%/29.4% (p < 0.0001) (2.4%/2.4% (n.s.)) hyperfunctioning, indifferent, hypofunctioning, and not rateable TNs for CDonly (CD+PET/US) and MD/MS, respectively. The respective rating confidence was indicated as absolute certain, quite certain, equivocal, uncertain, and not rateable in 11.7/3.4% (p < 0.0001) (44.9%/38.9% (p = 0.0541), 51.9%/26.7% (p < 0.0001) (46.2%/41.5% (n.s.)), 21.6%/29.0% (p = 0.0051) (6.2%/14.8% (p < 0.0001)), 1.1%/11.5% (p < 0.0001) (0.2%/2.3% (p = 0.0032)), and 13.7%/29.4% (p < 0.0001) (2.4%/2.4% (n.s.)) by MD/MS, respectively. There was a significant difference in the diversity of the observers’ functional assessment of TN (MD 0.84 vs. MS 1.02, p = 0.0006) and the respective confidence in functional assessment (MD 0.93 vs. MS 1.16, p < 0.0001) between MD and MS on CDonly, whereas CD+PET/US revealed weaker differences for both groups (MD 0.48 vs. MS 0.47, p = 0.57; and MD 0.66 vs. MS 0.83, p = 0.0437). With the additional application of I-124-PET/US, the rating diversity of both MD and MS markedly tends towards more consistency (p < 0.0001 in each case). Conclusion: The additional application of sensor-navigated I-124-PET/US fusion imaging significantly influenced the functional assessment of TN positively, especially for unexperienced observers. Full article

(This article belongs to the Special Issue Ultrasonic Systems for Biomedical Sensing)

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13 pages, 5295 KiB

Open AccessLetter

Design of an Ultrasound Transceiver ASIC with a Switching-Artifact Reduction Technique for 3D Carotid Artery Imaging

by Taehoon Kim, Fabian Fool, Djalma Simoes dos Santos, Zu-Yao Chang, Emile Noothout, Hendrik J. Vos, Johan G. Bosch, Martin D. Verweij, Nico de Jong and Michiel A. P. Pertijs

Sensors 2021, 21(1), 150; https://0-doi-org.brum.beds.ac.uk/10.3390/s21010150 - 29 Dec 2020

Cited by 7 | Viewed by 3522

Abstract

This paper presents an ultrasound transceiver application-specific integrated circuit (ASIC) directly integrated with an array of 12 × 80 piezoelectric transducer elements to enable next-generation ultrasound probes for 3D carotid artery imaging. The ASIC, implemented in a 0.18 µm high-voltage Bipolar-CMOS-DMOS (HV BCD) process, adopted a programmable switch matrix that allowed selected transducer elements in each row to be connected to a transmit and receive channel of an imaging system. This made the probe operate like an electronically translatable linear array, allowing large-aperture matrix arrays to be interfaced with a manageable number of system channels. This paper presents a second-generation ASIC that employed an improved switch design to minimize clock feedthrough and charge-injection effects of high-voltage metal–oxide–semiconductor field-effect transistors (HV MOSFETs), which in the first-generation ASIC caused parasitic transmissions and associated imaging artifacts. The proposed switch controller, implemented with cascaded non-overlapping clock generators, generated control signals with improved timing to mitigate the effects of these non-idealities. Both simulation results and electrical measurements showed a 20 dB reduction of the switching artifacts. In addition, an acoustic pulse-echo measurement successfully demonstrated a 20 dB reduction of imaging artifacts. Full article

(This article belongs to the Special Issue Ultrasonic Systems for Biomedical Sensing)

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