Büttner, Lars

Czarske, Jürgen

Nauber, Richard

English

Repositorium für Naturwissenschaften und Technik

Citation: Nauber, R.; Büttner, L.;Czarske, J. Special Issue onComputational Ultrasound Imagingand Applications. Appl. Sci. 2024, 14,964. https://doi.org/10.3390/app14030964Received: 16 January 2024Accepted: 18 January 2024Published: 23 January 2024Copyright: © 2024 by the authors.Licensee MDPI, Basel, Switzerland.This article is an open access articledistributed under the terms andconditions of the Creative CommonsAttribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).applied  sciencesEditorialSpecial Issue on Computational Ultrasound Imagingand ApplicationsRichard Nauber 1,2,* , Lars Büttner 2,* and Jürgen Czarske 2,3,*1 Leibniz Institute for Solid State and Materials Research, 01069 Dresden, Germany2 Laboratory for Measurement and Sensor System Technique, Faculty of Electrical and Computer Engineering,Technical University of Dresden, 01069 Dresden, Germany3 Institute of Applied Physics, Faculty of Natural Sciences, TU Dresden, 01062 Dresden, Germany* Correspondence: r.nauber@ifw-dresden.de (R.N.); lars.buettner@tu-dresden.de (L.B.);juergen.czarske@tu-dresden.de (J.C.)Scientific and technical progress is driven particularly by the ability to “look” intonew areas. Imaging technologies such as optical and electron microscopy, X-ray, positronemission tomography, magnetic resonance imaging, and most recently gravitational waveastronomy have each provided humanity with a window into a new world. Ultrasound(US) imaging, which emerged in the last century, has enabled us to probe otherwise opaquemedia in a non-invasive, safe, and cost-efficient manner. This has led to a multitude of newapplications, particularly in the fields of medical diagnostics and non-destructive testing.However, some practical limitations of ultrasound imaging have held some very desirableapplications just out of reach:1. Susceptibility to aberrations: The quality of a US image degrades if there are de-viations from the assumed speed of sound or reflections that are not accounted forduring beamforming. In the context of process metrology, for instance, having amulti-mode wave guide in the acoustical path to shield the transducer array from hotmelts prevents in situ flow imaging [1]. In medical context, the strong aberrationsinduced by the skull bone hinder transcranial US imaging and therapy [2]. Thislimitation impedes non-invasive, pre-hospital or bed-side diagnostics and continuousmonitoring of the brain.2. Limited processing bandwidth: The bandwidth of capturing and processing theinformation conveyed in the sound field is often limited by the ultrasound device.This makes it very hard to simultaneously achieve real-time 3D imaging with highspatial and temporal resolution over a large field of view. As a result, it is stillchallenging to comprehensibly capture fast-moving volumetric objects with complexstructures, such as the beating heart [3].3. Diffraction limit: The diffraction of sound waves limits the resolution of classical USimaging and hinders the ability to visualize sub-wavelength objects or structures. Byovercoming this limitation, anatomical and functional imaging of microvasculature invivo [4] or high-resolution flow mapping in technical processes [5] becomes feasible.In the future, this may even enable imaging and tracking of medical microrobots,which is essential for their application in vivo [6].4. Manual decision-making process: Deriving diagnostic decisions from ultrasoundimages is a complex and to date mostly manual process. Augmenting or automatingparts of the decision-making process through advanced statistical or machine learningmethods could potentially lead to faster and more objective diagnostic results [7].5. Limited modalities: Restriction to the classical modalities of US imaging, such asbrightness mode (B-mode) and Doppler, reduces its diagnostic value. Acquiringadditional modalities through computational or physical methods can provide moreinformation. For example, shear wave elastography can infer the mechanical stiff-ness of tissues and materials [8], and photoacoustic imaging can reveal their opticalproperties [9].Appl. Sci. 2024, 14, 964. https://doi.org/10.3390/app14030964 https://www.mdpi.com/journal/applsciAppl. Sci. 2024, 14, 964 2 of 3In recent decades, enormous computational resources have become available and costefficient. This allows addressing the aforementioned challenges with a combination ofnovel methods; for example, computational, software-defined ultrasound imaging allowsfor the use of more complex signal processing algorithms. Such methods enable super-resolution imaging, correction of strong aberrations, and reconstruction of the shear wavespeed of the insonified medium. Further down the signal processing pipeline, machinelearning methods can assist in interpreting the acquired data. This Special Issue comprisesa total of nine papers that address the aforementioned challenges.1. Mozaffarzadeh et al. show that geometry-based phase aberration correction enhancesthe contrast and resolution of transcranial images [10]. Nguyen Minh et al. show thatUS-based estimation of the thickness and speed of sound of the human tibia bone isimproved through phase aberration correction [11]. Doveri et al. establish reflection-mode ultrasound computed tomography for accurately mapping anatomical featuresdespite strong reflections and speed of sound differences [12].2. Kaddoura et al. develop a novel parallel transmission scheme that can decrease theacquisition time for 2D and 3D synthetic aperture imaging [13]. Zhang et al. introducealgorithmic improvements in a basic building block of US data processing for real-timeapplications [14].3. Weik et al. achieve super resolution flow imaging in liquid metals by utilizing ultra-sound localization microscopy [15].4. Kerdegari et al. automate the detection and localization of pulmonary abnormalitiesthrough deep learning with spatiotemporal attention in ultrasound videos [16]. Del-Canto-Fernández et al. establish image texture analysis as a US-based diagnosticsprotocol to gain insight into low back pain [17].5. Olteanu et al. use shear-wave elastography for diagnosing high-risk varices in non-alcoholic fatty liver disease based on the mechanical properties of the spleen [18].In summary, this Special Issue covers a multitude of computational ultrasound ap-proaches to address the limitations arising from restricted processing bandwidth, diffrac-tion, manual decision making, and restricted modalities. The nine papers primarily targetapplications in medical diagnostics, as well as technical and basic research uses. Compu-tational technologies are currently revolutionizing US imaging and extending its reachtowards new applications. Given the high rate of adoption of machine learning technolo-gies across the ultrasound processing pipeline, there is a growing demand for interpretableresults, particularly in the case of high-stakes decisions. Future research should be directedto provide reliable indicators of uncertainty to supplement any quantitative measures anddiagnostic results derived from ultrasound data.Funding: This research was partially funded by the German Research Foundation (DFG), projectnumbers 411799900 and 512483557, as well as by the European Research Council (ERC) under theEuropean Union’s Horizon 2020 research and innovation programme (Grant agreement No. 853609,"Micro-GIFT").Acknowledgments: The authors thank the many people who contributed to this Special Issue byeither submitting manuscripts, reviewing or handling them.Conflicts of Interest: The authors declare no conflict of interest.References1. Grüter, L.; Nauber, R.; Czarske, J. Ultrasonic Bubble Imaging in Molten Salt Using a Multi-Mode Waveguide and Time Reversal.IEEE Trans. Instrum. Meas. 2022, 71, 1–10. [CrossRef]2. Lindsey, B.D.; Nicoletto, H.A.; Bennett, E.R.; Laskowitz, D.T.; Smith, S.W. 3-D Transcranial Ultrasound Imaging with BilateralPhase Aberration Correction of Multiple Isoplanatic Patches: A Pilot Human Study with Microbubble Contrast Enhancement.Ultrasound Med. Biol. 2014, 40, 90–101. [CrossRef] [PubMed]3. Papadacci, C.; Pernot, M.; Couade, M.; Fink, M.; Tanter, M. High-contrast ultrafast imaging of the heart. IEEE Trans. Ultrason.Ferroelectr. Freq. Control. 2014, 61, 288–301. [CrossRef] [PubMed]Appl. Sci. 2024, 14, 964 3 of 34. Christensen-Jeffries, K.; Couture, O.; Dayton, P.A.; Eldar, Y.C.; Hynynen, K.; Kiessling, F.; O’Reilly, M.; Pinton, G.F.; Schmitz, G.;Tang, M.X.; et al. Super-resolution Ultrasound Imaging. Ultrasound Med. Biol. 2020, 46, 865–891. [CrossRef] [PubMed]5. Kupsch, C.; Feierabend, L.; Nauber, R.; Buttner, L.; Czarske, J. Ultrasound Super-Resolution Flow Measurement of Suspensionsin Narrow Channels. IEEE Trans. Ultrason. Ferroelectr. Freq. Control. 2021, 68, 807–817. [CrossRef] [PubMed]6. Nauber, R.; Goudu, S.R.; Goeckenjan, M.; Bornhäuser, M.; Ribeiro, C.; Medina-Sánchez, M. Medical microrobots in reproductivemedicine from the bench to the clinic. Nat. Commun. 2023, 14, 728. [CrossRef] [PubMed]7. Liu, S.; Wang, Y.; Yang, X.; Lei, B.; Liu, L.; Li, S.X.; Ni, D.; Wang, T. Deep Learning in Medical Ultrasound Analysis: A Review.Engineering 2019, 5, 261–275. [CrossRef]8. Garra, B.S. Elastography: history, principles, and technique comparison. Abdom. Imaging 2015, 40, 680–697. [CrossRef]9. Lin, L.; Wang, L.V. The emerging role of photoacoustic imaging in clinical oncology. Nat. Rev. Clin. Oncol. 2022, 19, 365–384.[CrossRef]10. Mozaffarzadeh, M.; Verweij, M.D.; de Jong, N.; Renaud, G. Comparison of Phase-Screen and Geometry-Based Phase AberrationCorrection Techniques for Real-Time Transcranial Ultrasound Imaging. Appl. Sci. 2022, 12, 10183. [CrossRef]11. Nguyen Minh, H.; Muller, M.; Raum, K. Estimation of Thickness and Speed of Sound for Transverse Cortical Bone Imaging UsingPhase Aberration Correction Methods: An In Silico and Ex Vivo Validation Study. Appl. Sci. 2022, 12, 5283. [CrossRef]12. Doveri, E.; Sabatier, L.; Long, V.; Lasaygues, P. Reflection-Mode Ultrasound Computed Tomography Based on Wavelet Processingfor High-Contrast Anatomical and Morphometric Imaging. Appl. Sci. 2021, 11, 9368. [CrossRef]13. Kaddoura, T.; Zemp, R.J. Hadamard Aperiodic Interval Codes for Parallel-Transmission 2D and 3D Synthetic Aperture UltrasoundImaging. Appl. Sci. 2022, 12, 4917. [CrossRef]14. Zhang, C.; Geng, X.; Yao, F.; Liu, L.; Guo, Z.; Zhang, Y.; Wang, Y. The Ultrasound Signal Processing Based on High-PerformanceCORDIC Algorithm and Radial Artery Imaging Implementation. Appl. Sci. 2023, 13, 5664. [CrossRef]15. Weik, D.; Grüter, L.; Räbiger, D.; Singh, S.; Vogt, T.; Eckert, S.; Czarske, J.; Büttner, L. Ultrasound Localization Microscopy inLiquid Metal Flows. Appl. Sci. 2022, 12, 4517. [CrossRef]16. Kerdegari, H.; Phung, N.T.H.; McBride, A.; Pisani, L.; Nguyen, H.V.; Duong, T.B.; Razavi, R.; Thwaites, L.; Yacoub, S.; Gomez, A.;et al. B-Line Detection and Localization in Lung Ultrasound Videos Using Spatiotemporal Attention. Appl. Sci. 2021, 11, 11697.[CrossRef]17. Del-Canto-Fernández, A.; Calleja-Martínez, P.; Descalzo-Hoyas, B.; Rodríguez-Posada, S.; Cuenca-Zaldívar, N.; Fernández-Carnero, S.; Naranjo-Cinto, F.; Gallego-Izquierdo, T. The Application of Image Texture Analysis Techniques on the Effects of DryNeedling versus Placebo in Low-Back Pain Patients: A Pilot-Study. Appl. Sci. 2022, 12, 5556. [CrossRef]18. Olteanu, V.A.; Sfarti, C.V.; Balan, G.G.; Timofte, O.; Gologan, E.; Mitrică, D.E.; Gilca-Blanariu, G.E.; Dascalu, C.G.; Sandu,I.; Ştefănescu, G. The Role of Shear-Wave Elastography of the Spleen in Ruling out the Presence of High-Risk Varices inNon-Alcoholic Fatty Liver Disease (NAFLD). Appl. Sci. 2023, 13, 5764. [CrossRef]Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individualauthor(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury topeople or property resulting from any ideas, methods, instructions or products referred to in the content.

Special Issue on Computational Ultrasound Imaging and Applications

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Special Issue on Computational Ultrasound Imaging and Applications

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