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Case Study 4: Quantitative Image Analysis – Novel Biomarkers for Clinical Trials and Diagnostics (IXICO)

Summary of the impact

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:

  1. The development of a spin-off company, IXICO, which has licenced the developed image analysis techniques and imaging biomarkers.
  2. The use of the image analysis techniques and imaging biomarkers in more than 40 clinical trials involving more than 10000 subject visits.
  3. The approval of imaging biomarkers by European regulators as a tool to enrich recruitment into regulated clinical trials in Alzheimer's disease (AD).

Submitting Institution

Imperial College London

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing
Medical and Health Sciences: Neurosciences

SIAscopy for rapid noninvasive in-vivo quantification and assessment of skin histology in dermatology and cosmetics

Summary of the impact

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.

Submitting Institution

University of Birmingham

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Technological

Research Subject Area(s)

Physical Sciences: Other Physical Sciences
Information and Computing Sciences: Artificial Intelligence and Image Processing
Medical and Health Sciences: Neurosciences

Robust and Accurate 2D-3D Image Registration

Summary of the impact

A collaborative research project between the Division of Imaging Sciences and Biomedical Engineering, King's College London (KCL) and Philips Healthcare has devised methods to register (i.e. align or match) pre-operative 3D computed tomography (CT) images to intraoperative 2D X-ray images, resulting in more accurate and robust registration/alignment measures. The measures can be applied directly to images from standard X-ray machines, allowing for rapid translation to guide surgical procedures and radiotherapy. These measures (or close variants) are used routinely in commercial products by Accuray, Philips Healthcare and Cydar Ltd (KCL spinout), benefitting the care of hundreds of patients worldwide, every day.

Submitting Institution

King's College London

Unit of Assessment

General Engineering

Summary Impact Type

Technological

Research Subject Area(s)

Physical Sciences: Other Physical Sciences
Information and Computing Sciences: Artificial Intelligence and Image Processing
Medical and Health Sciences: Neurosciences

Improving prostate cancer diagnosis and care using computer simulation and medical image registration

Summary of the impact

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.

Submitting Institution

University College London

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Health

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing
Engineering: Biomedical Engineering
Medical and Health Sciences: Neurosciences

Enhanced photo and special effects processing for professional and amateur photographers

Summary of the impact

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.

Submitting Institution

University College London

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing

Segmentation and Watermarking of Peripheral Blood Smear Images

Summary of the impact

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.

Submitting Institution

Liverpool Hope University

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Health

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing
Medical and Health Sciences: Cardiorespiratory Medicine and Haematology, Neurosciences

Platform for image-guided treatment of arrhythmia

Summary of the impact

Atrial fibrillation (AF), a form of cardiac rhythm disturbance, significantly increases risk of stroke, heart failure and sudden death. The Division of Imaging Sciences and Biomedical Engineering at King's College London and Philips Healthcare collaborated to develop a platform for guiding cardiovascular catheterisation procedures in patients with AF. The EP Navigator is a commercial, clinical product that integrates pre-acquired magnetic resonance and computer tomography images with real-time X-ray fluoroscopy. This enhances visualisation, thereby reducing procedure time and the patient's exposure to radiation. The EP Navigator is used in around 350 out of 2,000 centres worldwide that carry out ablation therapies for cardiac arrhythmias, despite strong competition.

Submitting Institution

King's College London

Unit of Assessment

General Engineering

Summary Impact Type

Technological

Research Subject Area(s)

Physical Sciences: Other Physical Sciences
Medical and Health Sciences: Cardiorespiratory Medicine and Haematology, Neurosciences

Phase Unwrapping Software

Summary of the impact

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.

Submitting Institution

Liverpool John Moores University

Unit of Assessment

General Engineering

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing
Medical and Health Sciences: Clinical Sciences

UOA15-10: Boujou: special effects software for the film industry

Summary of the impact

The Boujou special effects software was developed from research carried out at the Department of Engineering Science. It enables sophisticated computer generated imagery (CGI) to be quickly and easily added to `real' film footage, facilitating the visual effects that feature so importantly in films such as Harry Potter and X-Men. The software has become an essential tool used by film-makers, TV advert producers, and video game manufacturers, and for instance played a pivotal role in helping `The Curious Case of Benjamin Button' win the 2009 Oscar for Best Visual Effects. Between 2008 and 2013, sales of Boujou totalled £1.37 million and this software boosted productivity and profitability right across the global digital entertainment industry.

Submitting Institution

University of Oxford

Unit of Assessment

General Engineering

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing

Algorithms for Bio-imaging

Summary of the impact

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.

Submitting Institution

Middlesex University

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing
Engineering: Biomedical Engineering
Medical and Health Sciences: Neurosciences

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