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The key impact of this project, in the form of `proof of concept', has been by influencing the practice of medical professionals (haematologists) at the Transfusion Medicine & Immunohematology section (in the hospital wing) of the Christian Medical College (CMC) Vellore (India). This has been achieved by developing and implementing system software for segmenting (and watermarking) of the nuclei of the White Blood Cells (WBCs) of peripheral blood smear images to overcome the challenge of identifying various pathological conditions. Segmentation of medical images is a highly challenging process, especially when dealing with blood smear images, which are known to have a very complex cell structure. The project has led to a significant improvement in the work process of haematologists at CMC's hospital wing where the output of this research (software system pilot) is being used. This has had an impact on the way smear slides are digitised, archived, and includes the segmentation, analysis, and watermarking of medical images at CMC. Christian Medical College (CMC) and Hospital at Vellore is an educational and pioneering research institute and a tertiary care hospital (which is the CMC's hospital wing), located at Tamil Nadu in Southern India.
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.
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.
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:
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.
The body of research relating to perception and interpretation of medical images has generated a range of impacts on the practice and training of radiologists and reporting radiographers, with resultant benefits for patients. Engagement with the research findings has raised awareness in clinical practitioners of the implicit strategies they use during medical image interpretation and in particular the type and frequency of errors, including the prevalence of decision-making mistakes over issues of pathology perception. Practitioners have benefited through considering their individual strategies, leading to enhanced decision making processes and reducing error rates in interpretation of 2D and 3D images.
The impact has been achieved through engagement with the sector through relevant professional bodies, practitioner orientated publications and direct involvement of the research team in training and development activities for practitioners.
The impact of the research on practitioner diagnostic strategies is applicable across all areas of radiology and diagnostic radiography, but is also being explicitly pursued to determine training methods and assessment when radiologists view 3D Computed Tomography Colonography data for bowel cancer.
Our research on Active Shape Models (ASMs) and Active Appearance Models (AAMs) opened up a radically new approach to automated image interpretation, with applications in industrial inspection, medical image analysis, and face tracking/recognition. We identify:
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).
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.
Innovative algorithms to support the evaluation of gold immunochromomatographic assays have been applied in a test strip as part of medical devices to test for Down's syndrome and Acute Myocardial Infarction (AMI). The device has been used in China, with a total of over 4500 patients having used it in two city hospitals and in five county hospitals. The impact of the research has been to allow faster, cheaper and more accurate diagnosis. This has led to estimated savings of £10 per patient per test and improved accuracy of 9% across the period 2009-2012, compared to the use of the previously applied tests.