Precise scatterer localization for ultrasound contrast imaging

This thesis is concerned with developing algorithms for the precise localization of ultrasound point scatterers with an eye to super-resolution ultrasound contrast imaging. In medical ultrasound, the conventional resolution is limited by diffraction and, in contrast to other sensing fields, point source imaging has not been extensively investigated. Here, two independent methods were proposed aiming to increase the lateral and the axial resolution respectively, by improving the localization accuracy of a single scatterer. The methods were examined with simulated and experimental data by using standard transmission protocols. Where a technique is applicable to imaging of more complicated structures than point sources, this was also examined. Further, a preliminary study was included with algorithm application to microbubbles that are currently used in contrast enhanced ultrasound. It was demonstrated that it is feasible to translate to ultrasonics, adaptive processes or techniques from optical imaging/astronomy. This way, it was possible to overcome the diffraction limit and achieve sub-wavelength localization. The accuracy gains are subject to many parameters but may reach up to two orders of magnitude, and are based exclusively on array signal processing. The latter is an important advantage since current attempts for super-resolution ultrasound are image-based which is generally undesired

Imaging with therapeutic acoustic wavelets–short pulses enable acoustic localization when time of arrival is combined with delay and sum

—Passive acoustic mapping (PAM) is an algorithm that reconstructs the location of acoustic sources using an array of receivers. This technique can monitor therapeutic ultrasound procedures to confirm the spatial distribution and amount of microbubble activity induced. Current PAM algorithms have an excellentlateral resolution but have a poor axial resolution, making it difficult to distinguish acoustic sources within the ultrasound beams. With recent studies demonstrating that short-length and low-pressure pulses—acoustic wavelets—have the therapeutic function, we hypothesizedthat the axial resolution could be improved with a quasi-pulse-echo approach and that the resolution improvement would depend on the wavelet’s pulse length. This article describes an algorithm that resolves acoustic sources axially using time of flight and laterally using delayand-sum beamforming, which we named axial temporal position PAM (ATP-PAM). The algorithm accommodates a rapid short pulse (RaSP) sequence that can safely deliver drugs across the blood–brain barrier. We developed our algorithm with simulations (k-wave) and in vitro experiments for one-, two-, and five-cycle pulses, comparing our resolution against that of two current PAM algorithms. We then tested ATP-PAM in vivo and evaluated whether the reconstructed acoustic sources mapped to drug deliver

Clutter Mitigation in Echocardiography Using Sparse Signal Separation

In ultrasound imaging, clutter artifacts degrade images and may cause inaccurate diagnosis. In this paper, we apply a method called Morphological Component Analysis (MCA) for sparse signal separation with the objective of reducing such clutter artifacts. The MCA approach assumes that the two signals in the additive mix have each a sparse representation under some dictionary of atoms (a matrix), and separation is achieved by finding these sparse representations. In our work, an adaptive approach is used for learning the dictionary from the echo data. MCA is compared to Singular Value Filtering (SVF), a Principal Component Analysis- (PCA-) based filtering technique, and to a high-pass Finite Impulse Response (FIR) filter. Each filter is applied to a simulated hypoechoic lesion sequence, as well as experimental cardiac ultrasound data. MCA is demonstrated in both cases to outperform the FIR filter and obtain results comparable to the SVF method in terms of contrast-to-noise ratio (CNR). Furthermore, MCA shows a lower impact on tissue sections while removing the clutter artifacts. In experimental heart data, MCA obtains in our experiments clutter mitigation with an average CNR improvement of 1.33 dB

Autoenfoque en imagen ultrasónica

La inspección de componentes por ultrasonidos se realiza, actualmente, con sistemas de imagen phased array, versión industrial de los ecógrafos médicos. En ambos casos se utiliza un array con decenas o centenares de pequeños transductores piezoeléctricos que se controlan individualmente para enfocar y deflectar el haz ultrasónico en emisión y recepción. Pero, mientras que en medicina el array está en contacto con el cuerpo, que es flexible, en la industria se suele interponer un medio acoplante entre el array y el componente a inspeccionar. Cuando la geometría de la pieza no es plana se utiliza agua como medio acoplante, que se adapta a la forma de la pieza y proporciona un medio continuo y de baja atenuación para la transmisión del sonido. En estas condiciones existen dos medios de propagación, lo que dificulta la determinación de los retardos de enfoque por efectos de la refracción. Como en estas condiciones no existen fórmulas cerradas que faciliten su cálculo, hasta la fecha se han venido utilizando procesos iterativos computacionalmente costosos que impiden la modificación rápida del enfoque cuando varía la geometría de la pieza (por ejemplo, durante la realización de un barrido). Estas razones han impedido el desarrollo de técnicas de autoenfoque efectivas. Esta Tesis aporta tres técnicas que, junto al cálculo en tiempo real de los parámetros de enfoque y un soporte arquitectural de imagen a ultra-alta velocidad, están entre las primeras aproximaciones reales para solucionar el problema del autoenfoque en imagen ultrasónica. De hecho, una de ellas (AUTOFOCUS) ha sido patentada y transferida a la industria, que la comercializa en equipos phased array con esta capacidad. La memoria describe las motivaciones, fundamentos, aproximaciones conocidas al problema así como las dificultades y las soluciones investigadas. Una segunda parte incluye las publicaciones más relevantes donde se han comunicado los resultados, contrastando los teóricamente esperados con los experimentalmente obtenidos

Inverse Problem Formulation and Deep Learning Methods for Ultrasound Beamforming and Image Reconstruction

Ultrasound imaging is among the most common medical imaging modalities, which has the advantages of being real-time, non-invasive, cost-effective, and portable. Medical ultrasound images, however, have low values of signal-to-noise ratio due to many factors, and there has been a long-standing line of research on improving the quality of ultrasound images. Ultrasound transducers are made from piezoelectric elements, which are responsible for the insonification of the medium with non-invasive acoustic waves and also the reception of backscattered signals. Design optimizations span all steps of the image formation pipeline, including system architecture, hardware development, and software algorithms. Each step entails parameter optimizations and trade-offs in order to achieve a balance in competing effects such as cost, performance, and efficiency. The current thesis is devoted to research on image reconstruction techniques in order to push forward the classical limitations. It is tried not to be restricted into a specific class of computational imaging or machine learning method. As such, classical approaches and recent methods based on deep learning are adapted according to the requirements and limitations of the image reconstruction problem. In other words, we aim to reconstruct a high-quality spatial map of the medium echogenicity from raw channel data received from piezoelectric elements. All other steps of the ultrasound image formation pipeline are considered fixed, and the goal is to extract the best possible image quality (in terms of resolution, contrast, speckle pattern, etc.) from echo traces acquired by transducer elements. Two novel approaches are proposed on super-resolution ultrasound imaging by training deep models that create mapping functions from observations recorded from a single transmission to high-quality images. These models are mainly developed to resolve the necessity of several transmissions, which can potentially be used in applications that require both high framerate and image quality. The remaining four contributions are on beamforming, which is an essential step in medical ultrasound image reconstruction. Different approaches, including independent component analysis, deep learning, and inverse problem formulations, are utilized to tackle the ill-posed inverse problem of receive beamforming. The primary goal of novel beamformers is to find a solution to the trade-off between image quality and framerate. The final chapter consists of concluding remarks on each of our contributions, where the strengths and weaknesses of our proposed techniques based on classical computational imaging and deep learning methods are outlined. There is still a large room for improvement in all of our proposed techniques, and the thesis is concluded by providing avenues for future research to attain those improvements

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

Advancements and Breakthroughs in Ultrasound Imaging

Ultrasonic imaging is a powerful diagnostic tool available to medical practitioners, engineers and researchers today. Due to the relative safety, and the non-invasive nature, ultrasonic imaging has become one of the most rapidly advancing technologies. These rapid advances are directly related to the parallel advancements in electronics, computing, and transducer technology together with sophisticated signal processing techniques. This book focuses on state of the art developments in ultrasonic imaging applications and underlying technologies presented by leading practitioners and researchers from many parts of the world

Ultrasound and Photoacoustic Techniques for Surgical Guidance Inside and Around the Spine

Technological advances in image-guidance have made a significant impact in surgical standards, allowing for safer and less invasive procedures. Ultrasound and photoacoustic imaging are promising options for surgical guidance given their real-time capabilities without the use of ionizing radiation. However, challenges to improve the feasibility of ultrasound- and photoacoustic-based surgical guidance persists in the presence of bone. In this thesis, we address four challenges surrounding the implementation of ultrasound- and photoacoustic-based surgical guidance in clinical scenarios inside and around the spine. First, we introduce a novel regularized implementation of short-lag spatial coherence (SLSC) beamforming, named locally-weighted short-lag spatial coherence (LW-SLSC). LW-SLSC improves the segmentation of bony structures in ultrasound images, thus reducing the hardware and software cost of registering pre and intra-operative volumes. Second, we describe a contour analysis framework to characterize and differentiate photoacoustic signals originating from cancellous and cortical bone, which is critical for a safety navigation of surgical tools through small bony cavities such as the pedicle. This analysis is also useful for localizing tool tips within the pedicle. Third, we developed a GPU approach to SLSC beamforming to improve the signal-to-noise ratio of photoacoustic targets using low laser energies, thus improving the performance of robotic visual servoing of tooltips and enabling miniaturization of laser systems in the operating room. Finally, we developed a novel acoustic-based atlas method to identify photoacoustic contrast agents and discriminate them from tissue using only two laser wavelengths. This approach significantly reduces acquisition times in comparison to conventional spectral unmixing techniques. These four contributions are beneficial for the transition of a combined ultrasound and photoacoustic-based image-guidance system towards more challenging scenarios of surgical navigation. Focusing on bone structures inside and surrounding the spine, the newly combined systems and techniques demonstrated herein feature robust, accurate, and real-time capabilities to register to preoperative images, localize surgical tool tips, and characterize biomarkers. These contributions strengthen the range of possibilities for spinous and transthoracic ultrasound and photoacoustic navigation, broaden the scope of this field, and shorten the road to clinical implementation in the operating room