A Helmholtz equation solver using unsupervised learning: Application to transcranial ultrasound

Transcranial ultrasound therapy is increasingly used for the non-invasive treatment of brain disorders. However, conventional numerical wave solvers are currently too computationally expensive to be used online during treatments to predict the acoustic field passing through the skull (e.g., to account for subject-specific dose and targeting variations). As a step towards real-time predictions, in the current work, a fast iterative solver for the heterogeneous Helmholtz equation in 2D is developed using a fully-learned optimizer. The lightweight network architecture is based on a modified UNet that includes a learned hidden state. The network is trained using a physics-based loss function and a set of idealized sound speed distributions with fully unsupervised training (no knowledge of the true solution is required). The learned optimizer shows excellent performance on the test set, and is capable of generalization well outside the training examples, including to much larger computational domains, and more complex source and sound speed distributions, for example, those derived from x-ray computed tomography images of the skull.Comment: 23 pages, 13 figure

Imaging Sensors and Applications

In past decades, various sensor technologies have been used in all areas of our lives, thus improving our quality of life. In particular, imaging sensors have been widely applied in the development of various imaging approaches such as optical imaging, ultrasound imaging, X-ray imaging, and nuclear imaging, and contributed to achieve high sensitivity, miniaturization, and real-time imaging. These advanced image sensing technologies play an important role not only in the medical field but also in the industrial field. This Special Issue covers broad topics on imaging sensors and applications. The scope range of imaging sensors can be extended to novel imaging sensors and diverse imaging systems, including hardware and software advancements. Additionally, biomedical and nondestructive sensing applications are welcome

Transcranial Ultrasound Holograms for the Blood-Brain Barrier Opening

[ES] El tratamiento de enfermedades neurológicas está muy limitado por la ineficiente penetración de los fármacos en el tejido cerebral dañado debido a la barrera hematoencefálica (BHE), lo que imposibilita mejorar la salud del paciente. La BHE es un mecanismo de protección natural para evitar la difusión de agentes potencialmente peligrosas para el sistema nervioso central. No obstante, la BHE se puede inhibir mediante ultrasonidos focalizados e inyección de microburbujas de forma segura, localizada y transitoria, una tecnología empleada mundialmente. La principal ventaja es su carácter no invasivo, siendo así muy atractiva y cómoda para el paciente. Normalmente, la zona cerebral enferma se trata en su parte central empleando un único foco. Sin embargo, enfermedades como el Alzheimer o el Parkinson requieren un tratamiento sobre estructuras de geometría compleja y tamaño elevado, situadas en ambos hemisferios cerebrales. Por tanto, la tecnología actual está muy limitada al no cumplir dichos requisitos. Esta tesis doctoral tiene como objetivo el desarrollo de una técnica novedosa, basada en hologramas acústicos, para resolver las limitaciones presentes en los tratamientos neurológicos empleando ultrasonidos. Se estudian las lentes acústicas holográficas impresas en 3D, que acopladas a un transductor mono-elemento, permiten el control preciso del frente de onda ultrasónico tanto para (1) compensar las distorsiones que sufre el haz hasta alcanzar el cerebro, como (2) focalizarlo simultáneamente en regiones múltiples y de geometría compleja o formando de vórtices acústicos, proporcionando así efectividad en tiempo y coste. Por ello, la investigación desarrollada en esta tesis abre un camino prometedor en el campo de la biomedicina que permitirá mejorar los tratamientos neurológicos, además de aplicaciones en neuroestimulación o ablación térmica del tejido.[CA] El tractament de malalties neurològiques està molt limitat per la ineficient penetració del fàrmac en el teixit cerebral danyat a causa de la barrera hematoencefàlica (BHE), i així no és possible una millora de salut del pacient. La BHE és un mecanisme de protecció natural per a evitar la difusió d'agents potencialment perillosos per al Sistema Nervios Central. No obstant això, aquesta barrera es pot inhibir mitjancant una tecnologia emprada mundialment basada en ultrasons focalitzats i injeccio de microbombolles. El principal avantatge és el seu caràcter no invasiu, sent així molt atractiva i còmoda per al pacient, i permet obrir la BHE de manera segura, localitzada i transitòria. Normalment, la zona cerebral malalta es tracta en la seua part central, emprant un unic focus. No obstant això, malalties com l'Alzheimer o el Parkinson requereixen un tractament al llarg d'estructures de geometria complexa i grandària elevada, situades en tots dos hemisferis cerebrals. Per tant, la tecnologia actual està fortament limitada al no complir amb aquests requeriments. Aquesta tesi doctoral està enfocada a investigar i desenvolupar una tècnica nova, basada en hologrames acústics, per a solucionar les limitacions presents en els tractaments neurològics. Una lent acústica holograca de baix cost impresa en 3D acoblada a un transductor d'element simple permet el control precs del front d'ona ultrasònic punt per a (1) compensar les distorsions que pateix el feix en el seu camí cap al cervell, i (2) focalització simultània del feix en regions multiples i de geometria complexa, proporcionant aix un tractament efectiu en temps i cost. Per això, la investigació desenvolupada en aquesta tesi demostra la possibilitat de realitzar qualsevol tractament neurològic, a més d'aplicacions en la neuroestimulació o l'ablació tèrmica dins del camp biomèdic.[EN] Treatments for neurological diseases are strongly limited by the inefficient penetration of therapeutic drugs into the diseased brain due to the blood-brain barrier (BBB), and therefore no health improvement can be achieved. In fact, the BBB is a protection mechanism of the human body to avoid the diffusion of potentially dangerous agents into the central nervous system. Nevertheless, this barrier can be successfully inhibited by using a worldwide spread technology based on microbubble-enhanced focused ultrasound. Its main advantage is its non-invasive nature, thus defining a patient-friendly clinical procedure that allows to disrupt the BBB in a safe, local and transient manner. Conventionally, the diseased brain structure has been targeted in its center, with a single focus. However, Alzheimer's or Parkinson's Diseases do require that ultrasound is delivered to entire, complex-geometry and large-volume structures located at both hemispheres of the brain. Therefore, current technology presents several limitations as it does not fulfill these requirements. This doctoral thesis aims to develop a novel technique based on using focused ultrasound acoustic holograms to solve the existing limitations to treat neurological diseases. In this dissertation, we study 3D-printed holographic acoustic lenses coupled to a single-element transducer that allow to accurately control the acoustic wavefront to both (1) compensate distortions suffered by the beam in its path to the brain, and (2) simultaneous focusing in multiple and complex-geometry structures or acoustic vortex generation, providing a time- and cost- efficient procedure. Therefore, the research carried out throughout this thesis opens a promising path in the biomedical field to improve the treatment for neurological diseases, neurostimulation or tissue ablation applications.Acknowledgments to the Spanish institution Generalitat Valenciana, which funding grant allowed me to develop this doctoral thesis, and as well funded my research stay at Columbia University. The development of the entire thesis was supported through grant Nª. ACIF/2017/045. Particularly, the research carried out in Chapter 3 and Chapter 4 was possible thanks to and supported through grant BEFPI/2019/075. Action co-financied by the Agència Valenciana de la Innovació through grant INNVAL10/19/016 and by the European Union through the Programa Operativo del Fondo Europeo de Desarrollo Regional (FEDER) of the Comunitat Valenciana 2014-2020 (IDIFEDER/2018/022).Jiménez Gambín, S. (2021). Transcranial Ultrasound Holograms for the Blood-Brain Barrier Opening [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/171373TESI

医用超音波における散乱体分布の高解像かつ高感度な画像化に関する研究

Ultrasound imaging as an effective method is widely used in medical diagnosis andNDT (non-destructive testing). In particular, ultrasound imaging plays an important role in medical diagnosis due to its safety, noninvasive, inexpensiveness and real-time compared with other medical imaging techniques. However, in general the ultrasound imaging has more speckles and is low definition than the MRI (magnetic resonance imaging) and X-ray CT (computerized tomography). Therefore, it is important to improve the ultrasound imaging quality. In this study, there are three newproposals. The first is the development of a high sensitivity transducer that utilizes piezoelectric charge directly for FET (field effect transistor) channel control. The second is a proposal of a method for estimating the distribution of small scatterers in living tissue using the empirical Bayes method. The third is a super-resolution imagingmethod of scatterers with strong reflection such as organ boundaries and blood vessel walls. The specific description of each chapter is as follows: Chapter 1: The fundamental characteristics and the main applications of ultrasound are discussed, then the advantages and drawbacks of medical ultrasound are high-lighted. Based on the drawbacks, motivations and objectives of this study are stated. Chapter 2: To overcome disadvantages of medical ultrasound, we advanced our studyin two directions: designing new transducer improves the acquisition modality itself, onthe other hand new signal processing improve the acquired echo data. Therefore, the conventional techniques related to the two directions are reviewed. Chapter 3: For high performance piezoelectric, a structure that enables direct coupling of a PZT (lead zirconate titanate) element to the gate of a MOSFET (metal-oxide semiconductor field-effect transistor) to provide a device called the PZT-FET that acts as an ultrasound receiver was proposed. The experimental analysis of the PZT-FET, in terms of its reception sensitivity, dynamic range and -6 dB reception bandwidth have been investigated. The proposed PZT-FET receiver offers high sensitivity, wide dynamic range performance when compared to the typical ultrasound transducer. Chapter 4: In medical ultrasound imaging, speckle patterns caused by reflection interference from small scatterers in living tissue are often suppressed by various methodologies. However, accurate imaging of small scatterers is important in diagnosis; therefore, we investigated influence of speckle pattern on ultrasound imaging by the empirical Bayesian learning. Since small scatterers are spatially correlated and thereby constitute a microstructure, we assume that scatterers are distributed according to the AR (auto regressive) model with unknown parameters. Under this assumption, the AR parameters are estimated by maximizing the marginal likelihood function, and the scatterers distribution is estimated as a MAP (maximum a posteriori) estimator. The performance of our method is evaluated by simulations and experiments. Through the results, we confirmed that the band limited echo has sufficient information of the AR parameters and the power spectrum of the echoes from the scatterers is properly extrapolated. Chapter 5: The medical ultrasound imaging of strong reflectance scatterers based on the MUSIC algorithm is the main subject of Chapter 5. Previously, we have proposed a super-resolution ultrasound imaging based on multiple TRs (transmissions/receptions) with different carrier frequencies called SCM (super resolution FM-chirp correlation method). In order to reduce the number of required TRs for the SCM, the method has been extended to the SA (synthetic aperture) version called SA-SCM. However, since super-resolution processing is performed for each line data obtained by the RBF (reception beam forming) in the SA-SCM, image discontinuities tend to occur in the lateral direction. Therefore, a new method called SCM-weighted SA is proposed, in this version the SCM is performed on each transducer element, and then the SCM result is used as the weight for RBF. The SCM-weighted SA can generate multiple B-mode images each of which corresponds to each carrier frequency, and the appropriate low frequency images among them have no grating lobes. For a further improvement, instead of simple averaging, the SCM applied to the result of the SCM-weighted SA for all frequencies again, which is called SCM-weighted SA-SCM. We evaluated the effectiveness of all the methods by simulations and experiments. From the results, it can be confirmed that the extension of the SCM framework can help ultrasound imaging reduce grating lobes, perform super-resolution and better SNR(signal-to-noise ratio). Chapter 6: A discussion of the overall content of the thesis as well as suggestions for further development together with the remaining problems are summarized.首都大学東京, 2019-03-25, 博士（工学）首都大学東

U-Net and its variants for medical image segmentation: theory and applications

U-net is an image segmentation technique developed primarily for medical image analysis that can precisely segment images using a scarce amount of training data. These traits provide U-net with a very high utility within the medical imaging community and have resulted in extensive adoption of U-net as the primary tool for segmentation tasks in medical imaging. The success of U-net is evident in its widespread use in all major image modalities from CT scans and MRI to X-rays and microscopy. Furthermore, while U-net is largely a segmentation tool, there have been instances of the use of U-net in other applications. As the potential of U-net is still increasing, in this review we look at the various developments that have been made in the U-net architecture and provide observations on recent trends. We examine the various innovations that have been made in deep learning and discuss how these tools facilitate U-net. Furthermore, we look at image modalities and application areas where U-net has been applied.Comment: 42 pages, in IEEE Acces

Ultrasound in reverberating and aberrating environments: applications to human transcranial, transabdominal, and super-resolution imaging

Ultrasound imaging in the human body is degraded by effects of reverberation and aberration. The heterogeneous acoustical properties of different tissue types distort and reflect the wavefront as it travels to the target and as the echos travel back to the transducer. Transcranial imaging, has been a persistent challenge for ultrasound because the phase aberration, reverberation and attenuation from the human skull reduce the spatial resolution, to a millimeter or more, and limit contrast. Similar challenges arise in human abdominal imaging especially for patients with a large body mass index. Identifying, quantifying, and modeling these complex mechanisms of degradation are a critical component to develop rational strategies that can improve image quality. In this work, an experimental and simulation framework, calibrated to soft tissue measurements, that isolates and characterizes the individual sources of image degradation in ultrasound imaging is established. We show that using this simulation framework we can span the parameter space of image degradation in an independent or orthogonal fashion. Such flexibility offers advantages in the generation of training databases for machine learning applications as well as the development of beamforming strategies for challenging imaging scenarios. We also explored the framework's applications to lung ultrasound imaging, where the interpretation of reverberation artefacts occurring at the pleural surface is used to determine the underlying lung pathology. Using our acoustical simulation tools, B-mode images showcasing primary clinical features used in diagnostic lung imaging were successfully reproduced. These simulations establish a clear relationship of the artifacts to known underlying anatomical structures in a quantitative way. Transcranial simulations in 2D and 3D demonstrate that reverberations, whose role was previously unappreciated, are the principal source of image contrast and resolution degradation at shallow depths below 4~cm and when scattering tissue is present. Finally in the current work, the potential improvements offered by super-resolution imaging were explored by establishing the feasibility of transcranial super-resolution imaging through an intact human skull at a frequency of 2.5~MHz, with and without applying a phase correction, using with an existing clinical transducer.Doctor of Philosoph

Ultrasound for Material Characterization and Processing

Ultrasonic waves are nowadays used for multiple purposes including both low-intensity/high frequency and high-intensity/low-frequency ultrasound. Low-intensity ultrasound transmits energy through the medium in order to obtain information about the medium or to convey information through the medium. It is successfully used in non-destructive inspection, ultrasonic dynamic analysis, ultrasonic rheology, ultrasonic spectroscopy of materials, process monitoring, applications in civil engineering, aerospace and geological materials and structures, and in the characterization of biological media. Nowadays, it is an essential tool for assessing metals, plastics, aerospace composites, wood, concrete, and cement. High-intensity ultrasound deliberately affects the propagation medium through the high local temperatures and pressures generated. It is used in industrial processes such as welding, cleaning, emulsification, atomization, etc.; chemical reactions and reactor induced by ultrasonic waves; synthesis of organic and inorganic materials; microstructural effects; heat generation; accelerated material characterization by ultrasonic fatigue testing; food processing; and environmental protection. This book collects eleven papers, one review, and ten research papers with the aim to present recent advances in ultrasonic wave propagation applied for the characterization or the processing of materials. Both fundamental science and applications of ultrasound in the field of material characterization and material processing have been gathered

Ultrasound Imaging Innovations for Visualization and Quantification of Vascular Biomarkers

The existence of plaque in the carotid arteries, which provide circulation to the brain, is a known risk for stroke and dementia. Alas, this risk factor is present in 25% of the adult population. Proper assessment of carotid plaque may play a significant role in preventing and managing stroke and dementia. However, current plaque assessment routines have known limitations in assessing individual risk for future cardiovascular events. There is a practical need to derive new vascular biomarkers that are indicative of cardiovascular risk based on hemodynamic information. Nonetheless, the derivation of these biomarkers is not a trivial technical task because none of the existing clinical imaging modalities have adequate time resolution to track the spatiotemporal dynamics of arterial blood flow that is pulsatile in nature. The goal of this dissertation is to devise a new ultrasound imaging framework to measure vascular biomarkers related to turbulent flow, intra-plaque microvasculature, and blood flow rate. Central to the proposed framework is the use of high frame rate ultrasound (HiFRUS) imaging principles to track hemodynamic events at fine temporal resolution (through using frame rates of greater than 1000 frames per second). The existence of turbulent flow and intra-plaque microvessels, as well as anomalous blood flow rate, are all closely related to the formation and progression of carotid plaque. Therefore, quantifying these biomarkers can improve the identification of individuals with carotid plaque who are at risk for future cardiovascular events. To facilitate the testing and the implementation of the proposed imaging algorithms, this dissertation has included the development of new experimental models (in the form of flow phantoms) and a new HiFRUS imaging platform with live scanning and on-demand playback functionalities. Pilot studies were also carried out on rats and human volunteers. Results generally demonstrated the real-time performance and the practical efficacy of the proposed algorithms. The proposed ultrasound imaging framework is expected to improve carotid plaque risk classification and, in turn, facilitate timely identification of at-risk individuals. It may also be used to derive new insights on carotid plaque formation and progression to aid disease management and the development of personalized treatment strategies