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Our impact on the theory and practice of biometrics (identification of individuals through measurement/analysis of their physiological/behavioural characteristics) embraces contributions to technological development, to general systems-level principles and to public policy and professionalisation issues. Our research and consequent engagement across the stakeholder community has impacted on the technological development of practical biometrics through take-up by industry (e.g. InMezzo, one of the UK's leading secure information specialists, has enhanced identity authentication procedures), company spinout (the EFIT-V facial recognition suite from VisionMetric Ltd fundamentally changed the means by which facial composites are created and is now used by more than 85% of Britain's Police Forces), leadership of the development of standards for the expanding commercial marketplace (e.g. establishment of standards for image acquisition for e-passports and other access control applications) and policy-level input to Government and International Professional Bodies, providing long-term support for practical deployment and end- user engagement (the Biometrics Assurance Group with Fairhurst as an independent member reported the security risk and problems identifying fingerprints within the UK government's £5.6bn ID card scheme proposal).
UCL's research has led to changes in patient care for men with prostate cancer, through the implementation of less invasive, image-directed treatment and diagnostic strategies, and clinical trials that use these techniques. The use of medical image registration software to deliver high- intensity ultrasound therapy in a targeted manner has been shown to change the treatment plan in half of the patients participating in a clinical study. New biopsy criteria are now used routinely to classify patient risk at University College Hospital, where, since 2009, clinicians have determined the treatment options for more than 741 prostate cancer patients. The scheme has been adopted, by 15 other hospitals in the UK and internationally, where it has become the recommended standard of care, and has been used to treat more than 1,200 patients.
Researchers in the Department of Mathematics at Swansea University have developed novel geometric methods for image processing, feature extraction and shape interrogation. The research has delivered commercial and clinical impact in a variety of settings, ranging from new water marking techniques to improve piracy detection in the film industry, to medical research investigating the replacement of traditional CT scans with safer MR scans. The research has also delivered an automatic feature and gap detection tool that has been successfully applied to aircraft data files provided by BAE Systems. A consultancy company is exploiting the methods and a licence for the commercialisation of the technology is in process.
This Keele University research into advanced signal processing and classification methods has led to novel algorithms capable of isolating subtle patterns in complex data. This has been applied in two highly significant application areas: first to the problem of image source identification and second to the problem of unobtrusive but highly secure authentication methods. In the first case this has enabled images captured by mobile phone cameras to be reliably and evidentially linked to source devices. This has huge applicability to those fighting terrorism, paedophile rings and civil unrest by extending detection capabilities to mobile phones in an era in which they are rapidly replacing dedicated cameras. It helps to prove, for example, that a photograph entered as evidence was captured by a specific mobile phone. As most phones can be tied to their user or owner this is extremely important to the successful detection and prosecution of offenders.
In the second case it has enabled criminal record checks to be carried out securely online where previous paper-based systems were both too slow for purpose (taking weeks or months) and inherently insecure, leaving key posts unfilled in the health care industries and education sector; so benefitting the public by solving a problem that was having a negative impact on the running of these public services.
NIBEC connected health related research over the past 20 years has led to three high value spin- out companies. Their success is based on exploitation of over 35 NIBEC patents in medical sensors and electro-stimulation devices. Together these companies are currently valued at almost £100m, employ over 150 skilled people and have engineered medical innovations that have had global beneficial impact on health costs and patients' lives over these past four years. Our research is closely linked with international partners, commercial and clinical, has impacted local government policy through our leadership of the European Connected Health Alliance and has resulted in the £5m industry-focussed Connected Health Innovation Centre established at NIBEC.
Research at the University of Cambridge Department of Engineering on computer vision tracking led to the creation of Extra Reality Limited in 2010, which was subsequently acquired by a new company called Zappar Limited in May 2011. Zappar employs 17 staff and had revenue of GBP612k in the financial year 2012/13, an increase of 35% on the previous year.
Over 50 different brands have used Zappar's augmented reality application across more than 300 offerings in over 17 countries to deliver entertainment-based marketing interactions from 2011 to 2013. [text removed for publication] Examples of partners include Disney, Warner Brothers and Marvel. Zappar has changed attitudes in the media sector by showing that "augmented reality is finally ready for prime time" (President, Creative Strategies Inc, Time Online, 2012).
Professor Kautz and his team have developed two photo manipulation and processing methods (Exposure Fusion and local Laplacian filtering) that are used to produce well-exposed photographs with tuneable local contrast. Both are robust and consistent without requiring any per-image parameter tuning. Due to its reliability and effectiveness, Exposure Fusion is now considered the standard method for blending multiple photographs into a single well-exposed photograph, and is used by a large number of commercial and non-commercial products. Local Laplacian filtering was chosen by Adobe Systems Incorporated to be the default tool for image enhancements in Adobe Lightroom and Adobe Camera Raw. As a result, these methods are now in the hands of hundreds of thousands users, who use them to create and manipulate well-exposed digital photographs.
This case study describes how computational research in boundary problems at Middlesex was applied to bio-imaging using Electrical Impedance Tomography (EIT) for imaging brain function, lung function and tumour detection, and the development of Optical Tomography of brain function in neonates. This has resulted in the contribution of several public domain, open source resources to the international industrial and commercial research communities such as novel reconstruction algorithms, geometric models for generating accurate finite element and boundary element forward models and methods to generate subject-specific forward models which have been exploited as detailed below. It has also resulted in two patents.
A biomarker is a measurement or physical sign used as a substitute for a clinically meaningful endpoint that measures directly how a patient feels, functions, or survives. Biomarkers can be used to assess changes induced by a therapy or intervention on a clinically meaningful endpoint.
New quantitative image analysis techniques developed at Imperial College have enabled the computation of imaging biomarkers that are now widely used in clinical trials as well as for healthcare diagnostics. This case study illustrates the resulting key impacts including:
VisensiaTM is a bedside `early warning' system, deployed in many hospitals in the UK and US, which automatically analyses hospital patients' vital signs, produces simple-to-read scores, and alerts healthcare staff to any deterioration in a patient's condition. It resulted from research in this Department, commercialised by Oxford BioSignals Ltd (£1.5m sales to date, and 137 licences sold since 2010). VisensiaTM reduces the number of patients already in hospital who suffer an unexpected cardiac arrest or need an unplanned transfer to intensive care. The US Food and Drug Administration (FDA) approved the system's use after a 1000-patient clinical trial. There were no unexpected fatal cardiac arrests on the wards where the clinical trial took place in the three years after VisensiaTM. was deployed.