Ultrafast Ultrasound Imaging

Among medical imaging modalities, such as computed tomography (CT) and magnetic resonance imaging (MRI), ultrasound imaging stands out due to its temporal resolution. Owing to the nature of medical ultrasound imaging, it has been used for not only observation of the morphology of living organs but also functional imaging, such as blood flow imaging and evaluation of the cardiac function. Ultrafast ultrasound imaging, which has recently become widely available, significantly increases the opportunities for medical functional imaging. Ultrafast ultrasound imaging typically enables imaging frame-rates of up to ten thousand frames per second (fps). Due to the extremely high temporal resolution, this enables visualization of rapid dynamic responses of biological tissues, which cannot be observed and analyzed by conventional ultrasound imaging. This Special Issue includes various studies of improvements to the performance of ultrafast ultrasoun

Towards ultrasound full-waveform inversion in medical imaging

Ultrasound imaging is a front-line clinical modality with a wide range of applications. However, there are limitations to conventional methods for some medical imaging problems, including the imaging of the intact brain. The goal of this thesis is to explore and build on recent technological advances in ultrasonics and related areas such as geophysics, including the ultrasound data parallel acquisition hardware, advanced computational techniques for field modelling and for inverse problem solving. With the significant increase in the computational power now available, a particular focus will be put on exploring the potential of full-waveform inversion (FWI), a high-resolution image reconstruction technique which has shown significant success in seismic exploration, for medical imaging applications. In this thesis a range of technologies and systems have been developed in order to improve ultrasound imaging by taking advantage of these recent advances. In the first part of this thesis the application of dual frequency ultrasound for contrast enhanced imaging of neurovasculature in the mouse brain is investigated. Here we demonstrated a significant improvement in the contrast-to-tissue ratio that could be achieved by using a multi-probe, dual frequency imaging system when compared to a conventional approach using a single high frequency probe. However, without a sufficiently accurate calibration method to determine the positioning of these probes the image resolution was found to be significantly reduced. To mitigate the impact of these positioning errors, a second study was carried out to develop a sophisticated dual probe ultrasound tomography acquisition system with a robust methodology for the calibration of transducer positions. This led to a greater focus on the development of ultrasound tomography applications in medical imaging using FWI. A 2.5D brain phantom was designed that consisted of a soft tissue brain model surrounded by a hard skull mimicking material to simulate a transcranial imaging problem. This was used to demonstrate for the first time, as far as we are aware, the experimental feasibility of imaging the brain through skull using FWI. Furthermore, to address the lack of broadband sensors available for medical FWI reconstruction applications, a deep learning neural network was proposed for the bandwidth extension of observed narrowband data. A demonstration of this proposed technique was then carried out by improving the FWI image reconstruction of experimentally acquired breast phantom imaging data. Finally, the FWI imaging method was expanded for3D neuroimaging applications and an in silico feasibility of reconstructing the mouse brain with commercial transducers is demonstrated.Open Acces

Confidence-Driven Control of an Ultrasound Probe: Target-Specific Acoustic Window Optimization

International audienceWe propose a control framework to optimize the quality of robotic ultrasound imaging while tracking an anatomical target. We use a multitask approach to control the in-plane motion of a convex probe mounted on the end-effector of a robotic arm, based not only on the position of the target in the image, but also on features extracted from an ultrasound confidence map. The resulting control law therefore guarantees a good image quality, while keeping the target aligned with the central ultrasound scan-line. Potential applications of the proposed approach are, for example, teleoperated ultrasound examination, motion compensation for ultrasound-guided interventions , or automatic ultrasound acquisition. We demonstrate our approach with experiments on an ultrasound examination training phantom in motion

Robotic Ultrasound Imaging: State-of-the-Art and Future Perspectives

Ultrasound (US) is one of the most widely used modalities for clinical intervention and diagnosis due to the merits of providing non-invasive, radiation-free, and real-time images. However, free-hand US examinations are highly operator-dependent. Robotic US System (RUSS) aims at overcoming this shortcoming by offering reproducibility, while also aiming at improving dexterity, and intelligent anatomy and disease-aware imaging. In addition to enhancing diagnostic outcomes, RUSS also holds the potential to provide medical interventions for populations suffering from the shortage of experienced sonographers. In this paper, we categorize RUSS as teleoperated or autonomous. Regarding teleoperated RUSS, we summarize their technical developments, and clinical evaluations, respectively. This survey then focuses on the review of recent work on autonomous robotic US imaging. We demonstrate that machine learning and artificial intelligence present the key techniques, which enable intelligent patient and process-specific, motion and deformation-aware robotic image acquisition. We also show that the research on artificial intelligence for autonomous RUSS has directed the research community toward understanding and modeling expert sonographers' semantic reasoning and action. Here, we call this process, the recovery of the "language of sonography". This side result of research on autonomous robotic US acquisitions could be considered as valuable and essential as the progress made in the robotic US examination itself. This article will provide both engineers and clinicians with a comprehensive understanding of RUSS by surveying underlying techniques.Comment: Accepted by Medical Image Analysi