Understanding human skin appearance is a subject of great interest in science, medicine and technology. In medicine, skin appearance is a vital factor in surgical/prosthetic reconstruction, medical make-up/tattooing and disease diagnosis. The production of facial prostheses to replace missing facial structures requires the skills of highly trained anaplastologists to correctly match the shape and colour of the prosthesis to that of the host skin. With the 3D printing of human skin now available the process involved in matching natural and manufactured skin samples has become essential; a robust, accurate and efficient imaging system is required that acquires the relevant skin information and predicts a good match and translates this information through this new and innovative manufacturing process. A major problem with manufactured skin is that the match to the individual's natural skin must hold not only be accurate under a particular ambient illumination but the match needs to be preserved when the individual is moving between different environments, e.g. when the individual moves from office or LED lighting into daylight. To achieve this illumination invariance, the physical properties of the skin need to be taken into account. A further requirement for successful skin reproduction is the development of appearance models. These can be considered as individual "recipes' or 'blueprints" for each skin type and these not only represent inter-personal differences - different ethnic groups and age ranges, but also intra-personal differences - for each individual. Features of the human skin (wrinkles, pores, freckles, spots etc) make human skin as individual as a finger prints and thus, for facial prosthetics applications, skin appearance models also need to be fine-tuned for each individual area. The purpose of this work is to develop a complete spectral-based 3D imaging system which will allow us to additively manufacture soft tissue prosthetics or deliver predictable tattooing techniques that will exactly match the skin colour of a particular individual (Application 1) or have the capability to rapidly manufacture/3D print soft tissue replacements representative of a particular ethnic/age/gender group with a high degree of accuracy (Application 2). In application 1, the input to this 3D imaging system will consist of a 3D colour skin image (of a particular individual) obtained with a 3D camera in conjunction other specific skin characteristics. The skin sample will then be printed using a printer profile that maximises the match between the natural and printed skin across different ambient illuminations. In application 2, the skin manufacturing process will not be fine-tuned for a particular individual, but input to the 3D imaging system will consist of basic information about the age, gender and ethnicity. Representative skin samples (colour; texture; translucency; geometry) for this group will then be loaded from a pre-computed library instead of using the measurements from an individual.

Radiotherapy kills cancerous cells by repeatedly targeting a tumour with high energy radiation. Although image assisted pre-treatment planning based on CT is performed to minimise the amount of healthy tissues being irradiated, the planned treatment is delivered in a manner that is effectively blind, because there is no monitoring of the patient motion and internal anatomy during radiation treatment delivery and no, dynamically modelled, consideration of possible body change during treatment period. This uncomfortable state of affairs persists worldwide, despite complex new treatments and image guided radiotherapy (IGRT) which members of the consortium helped to develop. Furthermore, there is a concern on the additional imaging radiation dose to the patient from the IGRT. Hence, the MEGURATH project was proposed to introduce metrology guided radiotherapy (MGRT), where the patient is measured, imaged and modelled during treatment delivery via optical sensing to provide non-invasive, radiation-free, real-time 3D patient position monitoring, and dynamic deformation modelling to determine the internal anatomical changes. The project is considered as a significant one with a leap forward approach for a grand challenge, and has attracted interest from Elekta Oncology Systems, Philips Medical Systems, VisionRT and NHS-IP.The MEGRATH programme consists of not only comprehensive research activities with diverse theoretical topics, but also translation of science and technology to the first purpose built IGRT research facility in the UK at the Christie Hospital, and the support of clinical studies selected from breast, lung, bowel, prostate and bladder cancers. The project is expected to make a world class contribution to radiotherapy by increasing our understanding of tumour target and organ at risk behaviour, treatment delivery and control of their impact on cure and complications. The marriage of anatomical modelling and dynamic 3D measurement on demand 'in-treatment', using light rather than ionising radiation like X-rays, will offer the opportunity to gain the pole position in engineering and computational science for oncology. The Collaborating for Success through People call is a valuable opportunity to support, complement, utilise and extend the MEGURATH project, thereby enabling the consortium to maintain, defend and widen its lead.The proposed programme of people-based activities starts with exploratory mutual visits by the PIs and group leaders for exchange of knowledge, creation of ideas and development of active collaboration, followed by two-way investigative short visits and relatively long research visits by researchers for synergistic development, cross application and performance evaluation of promising approaches, and finished by a workshop to provide a venue for the consortium to lead the development of a joint EU project proposal with the participating partners. To provide significant added value to the MEGURATH project in terms of scientific knowledge and new clinical applications, 7 eminent research groups and 1 leading 3D equipment company are selected for participation in the proposed people-based activities:-Two from Poland: Telemedicine Group from AGH University of Science and Technology, and Department of Scientific Information from Jagiellonian University Collegium Medicum;-Three from France: one from the French National Institute for Research in Computer Science and Control (INRIA), and the other two from National Centre for Scientific Research (CRNS), namely, Lyon Research Centre for Images and Intelligent Information Systems (LIRIS) and Signal and Image Processing Research Laboratory (ETIS);-One from Germany: Institute for Electronics Signal Processing and Communications (IESK) at Otto von Guericke Universitt Magdeburg; -One from Italy: Signals and Images Laboratory from the National Research Council (CNR); and-3dMD with the company headquarters in the USA.

To maintain continuity with MATCH Phase 1, it has been requested that MATCH Phase 2 follows the current programme breakdown in terms of Projects A-F from 2008-2013 / a vision that is described below. We note that MATCH changed dramatically in creating the projects A-F and that further changes in the themes are inevitable. An overview of these themes is given below.Projects A, B and C address economic evaluation and its impact in decision-making by companies, governments and procurement agencies. We have identified a major demand for such research, but note that there is some convergence between these themes (for instance, A and C may well coalesce under the Bayesian banner). In particular, a 'methodologies' theme is likely to emerge in this. Under the former theme, a truly integrated Bayesian framework for medical devices would represent a strategically important achievement.On the other hand, the business of delivering these developments to industry, and the organisations or franchises that might ultimately provide the best vehicle for doing so, still requires further exploration and negotiation, and at this point there is considerable uncertainty about how this will best be done. However the critical element has been established, namely that MATCH can provide useful tools for, and attract significant levels of funding from industry. To this extent, the applied side of Project A-F and Project 5 might well evolve into a series of programmes designed to spin out tools, training and best practice into industry. Project 5 remains for the present because we have set it up with a framework within which company IP can be protected, and within which we can expedite projects to company goals and time scales.A similar pattern is likely to emerge from the single User project (D), where there is considerable scope for capability, and methodological development / and the size of this team needs to increase. The aim is to develop a suite of methods, guidelines and examples, describing when a given method is useful and when user needs assessment must be cost-effective. We will gain and share experience on what approach works best where. Our taxonomy will recognise circumstances where the novelty of a proposed device may undermine the validity of user needs assessment conducted before the 'technological push' has had a fair opportunity to impact on the human imagination.Moreover, new research is needed to 'glue' some of these themes together. Some of this is already included (for instance, in Projects C and D below) to link the user-facing social science with the economics, or the pathway-changing experiences (F) with formal economic evaluation, will require new, cross-disciplinary research. This type of research is essential to developing the shared view of value, which MATCH is pursuing. Similarly, integrating supply-chain decision-making and procurement elements of theme (E) with economic evaluation would represent an important element of unification.To achieve this, we will need to bring in some news skills. For instance, we are already freeing up some funding to bring in an economics researcher at Ulster; more statistical mathematical support may be needed to further develop the Bayesian theme; and we need to bolster the sociological element within the team.Finally, this vision cannot be funded entirely within a research framework, and we expect critical elements to be achieved under other funding (for instance, Theme E by the NHS, in due course).