The range of surgical tools for interventional procedures that dissect or fragment tissue has not changed significantly for millennia. There is huge potential for ultrasonic devices to enable new minimal access surgeries, offering higher precision, much lower force, better preservation of delicate structures, low thermal damage and, importantly, enabling more procedures to be carried out on an out-patient or day surgery basis. To realise this potential, and deliver our vision of ultrasonics being the technology of choice for minimal access interventional surgery, a completely new approach to device design is required, to achieve miniaturisation and to incorporate both a cutting and healing capability in the devices. By integrating with innovative flexible, tentacle-like surgical robots, we will bring ultrasonic devices deep into the human body, along tortuous pathways to the surgical site, to deliver unparalleled precision. Unsurpassed precision in challenging neurological, skull-base and spinal procedures as well as in general surgery is attainable through tailoring the robotic-ultrasonic devices to deliver the exact ultrasonic energy to the exact locations required to optimise the surgery. We will achieve this by quantifying the effects of the ultrasonic excitations typical of surgical devices in tissues, at and surrounding the site of surgery, in terms of precision cutting, tissue damage (mechanical damage, thermal necrosis, cavitation) but also the potential to aid regeneration. We will make world-leading advances in ultra-high speed imaging measurements and biophysical analysis, complementing advances in histology and clinical assessment, to develop a combined approach to the characterisation of both damage and regeneration of tissue. Through this holistic approach to device design, we will create integrated robotic-ultrasonic surgical devices tailored for optimised surgery.

Manufacturing is a key activity of the UK economy and accounts for more than half of all UK exports. The ability to reliably test components at every stage, from manufacture to end of service, is crucial for maximising economic growth, minimising environmental impact and ensuring public safety. End of life inspection is particularly important as much of the UK's infrastructure is ageing and, due to global financial pressures, cannot be replaced. Thus, the lifetimes of key UK assets, such as nuclear plants, must be extended. Ultrasonic non-destructive testing presents an economically and environmentally desirable solution for detecting damage in such components. Similar to medical ultrasound, ultrasonic waves can be passed through industrial components and subsequently collected, without damaging their internal composition. Large networks of sensors, typically arranged in linear arrays, are deployed to carry out these inspections, resulting in large volume, noisy, time-series data. Mathematical algorithms are then required to decipher the information encoded within these recorded signals and construct images of the component's interior. Such algorithms are fundamental enablers of the fourth industrial revolution facilitated by robotics and automated systems, which are largely dependent on accurate sensing, measurement and imaging systems. In many cases, the component under inspection exhibits an anisotropic, heterogeneous microstructure (that is, the material properties are directionally dependent and vary spatially in a random fashion). This is detrimental to standard imaging methodologies as the ultrasonic wave is bent and scattered by microstructural features and the responses from defects are obscured. Examples of such difficult to inspect materials include coarse grained steel welds and carbon-fibre reinforced polymer (CFRP) composites. In fact, materials with complex and highly scattering microstructures are becoming increasingly common as industries continue to invest in the development of lighter, stronger composite materials. To combat the difficulties in imaging within these materials, the current, cutting-edge imaging research within the NDT community endeavours to map the spatially varying material properties using time of flight tomography. However, time-of-flight tomography uses only one data point from each recorded time series and thus does not fully exploit the wealth of information made available by the inspection. The first objective of the proposed research is to develop a material mapping methodology which exploits the full recorded signal, addressing the non-uniqueness issues faced by time-of-flight tomography. This will be achieved via the development of new mathematical models that capture the varying properties of heterogeneous media using probability theory and stochastic models. The resulting material maps will then be incorporated into an advanced imaging system whereby the deviation of the ultrasonic wave path in the heterogeneous media can be corrected for so that reliable defect detection can be ensured. The second objective of the proposed research is to create an algorithm which can reconstruct complete datasets from incomplete observations using novel matrix and tensor completion techniques (an emerging area within data-science), facilitating faster inspection times and real-time imaging.