Development of a real-time ultrasonic sensing system for automated and robotic welding

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The implementation of robotic technology into welding processes is made difficult by the inherent process variables of part location, fit up, orientation and repeatability. Considering these aspects, to ensure weld reproducibility consistency and quality, advanced adaptive control techniques are essential. These involve not only the development of adequate sensors for seam tracking and joint recognition but also developments of overall machines with a level of artificial intelligence sufficient for automated welding. The development of such a prototype system which utilizes a manipulator arm, ultrasonic sensors and a transistorised welding power source is outlined. This system incorporates three essential aspects. It locates and tracks the welding seam ensuring correct positioning of the welding head relatively to the joint preparation. Additionally, it monitors the joint profile of the molten weld pool and modifies the relevant heat input parameters ensuring consistent penetration, joint filling and acceptable weld bead shape. Finally, it makes use of both the above information to reconstruct three-dimensional images of the weld pool silhouettes providing in-process inspection capabilities of the welded joints. Welding process control strategies have been incorporated into the system based on quantitative relationships between input parameters and weld bead shape configuration allowing real-time decisions to be made during the process of welding, without the need for operation intervention.British Technology Group (BTG

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

Volumetric MRI Reconstruction from 2D Slices in the Presence of Motion

Despite recent advances in acquisition techniques and reconstruction algorithms, magnetic resonance imaging (MRI) remains challenging in the presence of motion. To mitigate this, ultra-fast two-dimensional (2D) MRI sequences are often used in clinical practice to acquire thick, low-resolution (LR) 2D slices to reduce in-plane motion. The resulting stacks of thick 2D slices typically provide high-quality visualizations when viewed in the in-plane direction. However, the low spatial resolution in the through-plane direction in combination with motion commonly occurring between individual slice acquisitions gives rise to stacks with overall limited geometric integrity. In further consequence, an accurate and reliable diagnosis may be compromised when using such motion-corrupted, thick-slice MRI data. This thesis presents methods to volumetrically reconstruct geometrically consistent, high-resolution (HR) three-dimensional (3D) images from motion-corrupted, possibly sparse, low-resolution 2D MR slices. It focuses on volumetric reconstructions techniques using inverse problem formulations applicable to a broad field of clinical applications in which associated motion patterns are inherently different, but the use of thick-slice MR data is current clinical practice. In particular, volumetric reconstruction frameworks are developed based on slice-to-volume registration with inter-slice transformation regularization and robust, complete-outlier rejection for the reconstruction step that can either avoid or efficiently deal with potential slice-misregistrations. Additionally, this thesis describes efficient Forward-Backward Splitting schemes for image registration for any combination of differentiable (not necessarily convex) similarity measure and convex (not necessarily smooth) regularization with a tractable proximal operator. Experiments are performed on fetal and upper abdominal MRI, and on historical, printed brain MR films associated with a uniquely long-term study dating back to the 1980s. The results demonstrate the broad applicability of the presented frameworks to achieve robust reconstructions with the potential to improve disease diagnosis and patient management in clinical practice

30th International Conference on Condition Monitoring and Diagnostic Engineering Management (COMADEM 2017)

Proceedings of COMADEM 201

Moving beyond DTI: non-gaussian diffusion in the brain and skeletal muscle

Diffusion Magnetic Resonance Imaging (dMRI) is a diagnostic technique able to provide in- vivo measures that are related to the microstructure of tissues. Thanks to the sensitivity to microstructural tissue changes, Diffusion Weighted Imaging (DWI) and derived metrics, as the Apparent Diffusion Coefficient (ADC) , became the gold standard for the detection of strokes and ischemia since the early 90‟s. In 1994 Basser and colleagues introduced Diffusion Tensor Imaging (DTI), the first quantification approach able to capture the anisotropy of the diffusion process in in-vivo biological tissues. Chapter II shows the results we obtained applying DTI to investigate white matter alterations of a population affected by Friedreich‟s Ataxia. After more than 20 years from its introduction, DTI is still widely applied. However, concerns about the limitations of the technique have been increasingly risen over-time, with particular reference to the lack of specificity of the model and the coexistence of tissues with multiple architectures. Additionally, the tensor model can be applied only to a range of “moderate” diffusion sensitizations, after which the presence of biological membranes becomes non-negligible and gives origin to phenomena of “non-Gaussian diffusion”, that violate the assumptions of the model. Chapter III and Chapter IV deal specifically with these limitations, addressing the problem with two different approaches and applications. Another popular technique to investigate the dMRI signal is Spherical Deconvolution (SD), that in Chapter IV is presented in a tissue specific formulation and applied to derive diffusivity metrics specific to white matter, gray matter and cerebrospinal fluid, both in healthy controls and in a patient affected by MS. Since the early days of dMRI, experiments have been performed not only in the brain but in several body districts, including the skeletal muscle. Back in 1986 Le Bihan et al. observed that the water flowing in the micro vascular network and in the vessels was contributing to the acquisition of data at very low diffusion sensitization, and proposed the “Intra- Voxel Incoherent Motion” (IVIM) model. IVIM can be seen either as a model to obtain measures of pseudo-diffusion, or as a technique to obtain perfusion free ADC measures, thus recognizing it as an artifact. Although dMRI and DTI were applied to the skeletal muscle since its early days, later evolutions as Diffusion Kurtosis Imaging have only recently been applied to the skeletal muscle to fit dMRI data acquired at strong diffusion sensitization. The concepts of IVIM and DKI are developed in Chapter V, where the effects of the first on DTI and DKI, as well as the relation between DTI and DKI metrics are investigated through simulations and MRI data of the calf. In line with the current dMRI literature, the first 5 chapters of this thesis depict the diffusion signal as a complex measure arising from multiple tissue components. Chapter VI investigates a multi-compartment pseudo-continuous deconvolution approach, a technique that does not require explicit modeling of the tissues. Finally, Chapter VII presents an overview of other research topics I have work on during the PhD

Objective localisation of oral mucosal lesions using optical coherence tomography.

PhDIdentification of the most representative location for biopsy is critical in establishing the definitive diagnosis of oral mucosal lesions. Currently, this process involves visual evaluation of the colour characteristics of tissue aided by topical application of contrast enhancing agents. Although, this approach is widely practiced, it remains limited by its lack of objectivity in identifying and delineating suspicious areas for biopsy. To overcome this drawback there is a need to introduce a technique that would provide macroscopic guidance based on microscopic imaging and analysis. Optical Coherence Tomography is an emerging high resolution biomedical imaging modality that can potentially be used as an in vivo tool for selection of the most appropriate site for biopsy. This thesis investigates the use of OCT for qualitative and quantitative mapping of oral mucosal lesions. Feasibility studies were performed on patient biopsy samples prior to histopathological processing using a commercial OCT microscope. Qualitative imaging results examining a variety of normal, benign, inflammatory and premalignant lesions of the oral mucosa will be presented. Furthermore, the identification and utilisation of a common quantifiable parameter in OCT and histology of images of normal and dysplastic oral epithelium will be explored thus ensuring objective and reproducible mapping of the progression of oral carcinogenesis. Finally, the selection of the most representative biopsy site of oral epithelial dysplasia would be investigated using a novel approach, scattering attenuation microscopy. It is hoped this approach may help convey more clinical meaning than the conventional visualisation of OCT images

Advanced Techniques for Ground Penetrating Radar Imaging

Ground penetrating radar (GPR) has become one of the key technologies in subsurface sensing and, in general, in non-destructive testing (NDT), since it is able to detect both metallic and nonmetallic targets. GPR for NDT has been successfully introduced in a wide range of sectors, such as mining and geology, glaciology, civil engineering and civil works, archaeology, and security and defense. In recent decades, improvements in georeferencing and positioning systems have enabled the introduction of synthetic aperture radar (SAR) techniques in GPR systems, yielding GPR–SAR systems capable of providing high-resolution microwave images. In parallel, the radiofrequency front-end of GPR systems has been optimized in terms of compactness (e.g., smaller Tx/Rx antennas) and cost. These advances, combined with improvements in autonomous platforms, such as unmanned terrestrial and aerial vehicles, have fostered new fields of application for GPR, where fast and reliable detection capabilities are demanded. In addition, processing techniques have been improved, taking advantage of the research conducted in related fields like inverse scattering and imaging. As a result, novel and robust algorithms have been developed for clutter reduction, automatic target recognition, and efficient processing of large sets of measurements to enable real-time imaging, among others. This Special Issue provides an overview of the state of the art in GPR imaging, focusing on the latest advances from both hardware and software perspectives

Optical Coherence Tomography and Its Non-medical Applications

Optical coherence tomography (OCT) is a promising non-invasive non-contact 3D imaging technique that can be used to evaluate and inspect material surfaces, multilayer polymer films, fiber coils, and coatings. OCT can be used for the examination of cultural heritage objects and 3D imaging of microstructures. With subsurface 3D fingerprint imaging capability, OCT could be a valuable tool for enhancing security in biometric applications. OCT can also be used for the evaluation of fastener flushness for improving aerodynamic performance of high-speed aircraft. More and more OCT non-medical applications are emerging. In this book, we present some recent advancements in OCT technology and non-medical applications