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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:
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 Keele University research in multiscale object recognition has led to two key breakthroughs: (a) the automated identification of tissue boundaries in computer tomographic (CT) scans, enabling the latest radiotherapy equipment to more accurately target diseased tissue thus avoiding neighbouring healthy organs. Such improvements are essential to the successful roll-out of new more precise linear accelerators in the treatment of cancer; (b) new fractal algorithms to characterise the quality of transplanted cell growth from post-operative biopsies. By automating the selection of the healthiest cells this has assisted the generation of patient-specific cartilage and is essential for the development of a medical capability for large-scale patient-specific generation of cartilage growth for the treatment of arthritis. It has indirectly led to software improvements in cell-tracking and to achieving reliable auto-focussing in high throughput non-invasive microscopy.
Key advances in the earlier diagnosis of cancer, leading to better treatment and higher survival rates, have resulted from the commercialisation of unique imaging software that exploits research from the Department of Engineering Science. The software products that came from this research, Volpara™, XD and XRT are now used at major cancer centres worldwide (with approximately 1100 software installations), aiding treatment of tens of thousands of patients every year. Between 2009 and July 2013, Volpara™ scanned over 1.2 million mammograms, enabling the early detection of around 1800 cancers. The products' success has catalysed significant improvements in cancer care, and generated an estimated £9M in sales over the past two years for the spinout companies established to develop them (Matakina, based in New Zealand, and Mirada Medical, based in the UK).
SIAscopy is an image analysis method using the physics of image formation. It non-invasively provides near-instant quantitative maps of the key histological components of the skin. The scientific underpinnings were developed by Prof. Claridge's group, patented, and commercialised via a spin-off company Astron Clinica. SIAscopy was incorporated into medical imaging products which improved accuracy of general practitioners in diagnosis of melanoma, a skin cancer, whilst delivering higher cost-effectiveness than best clinical practice. Developed primarily for cancer diagnosis, SIAscopy also found uses in the cosmetics industry. In 2011 the current IPR owner, MedX, estimated the US market opportunity for the technology to be around $1 Billion.
Led from Dundee by Prof Jason Swedlow FRSE, The Open Microscopy Environment (OME) is an international consortium building tools to enable the storage and analysis of biological image data. OME releases Bio-Formats, an image format translation library, and OMERO, software for the visualisation, management and analysis of image data recorded by microscopes and high-content screening systems. OME software is open-source and transforms the way researchers manage the vast amount of image data routinely produced in research laboratories. Glencoe Software is the commercial arm of OME and provides commercial licenses, support, and customisation for OME's software tools to major industrial customers.
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.
Phase unwrapping is an essential algorithmic step in any measurement system or sensor that seeks to determine continuous phase. Instances of such devices are widespread: e.g. image reconstruction in magnetic resonance imaging (MRI), synthetic aperture radar (SAR) by satellite systems, analysis of seismic data in geophysics and optical instrumentation, to name but a few. Without successfully solving the phase unwrapping problem these instruments cannot function.
The topic is well developed and competition among algorithms is fierce. In 2012 alone, some 235 papers, most of which were describing potential new algorithms, were published in the area. But the continuing need for high-speed, automated and robust unwrapping algorithms poses a major limitation on the employability of phase measuring systems.
Working originally within the context of structured light 3D measurement systems, our research has developed new phase image unwrapping algorithms that constitute significance advances in speed, automation and robustness. The work has led to adoption by industry, as well as use in commercial and government research centres around the globe. Our approach since 2010 has been to make these algorithms freely available to end users. Third parties have gone on to translate our algorithms into other languages, widely used numerical software libraries have incorporated the algorithms and there are high profile industrial users.
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.
Video surveillance or monitoring is an important ingredient of modern life. Research conducted by the 2017Centre for Information, Intelligence and Security Systems` (CIISS), into improving the reliability of automated detection of visual entities in videos, has made an impact on public services and on practitioners (increased speed and quality, lower labour cost — Beneficiaries: U.K. Police; police investigators) and their health (mitigation of potential physical or psychological harm — Beneficiaries: police investigators), on society (reduction of a factor associated with crime rates and legal costs — Beneficiaries: the public; tax-payers), and on business (creation of a spin-out company - Adaptive Video Analytics Technologies Ltd — Beneficiaries: UK; and influence on management decisions about technology choices — Beneficiaries: Serco Group plc (HMP Dovegate)).