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
over issues of pathology perception. Practitioners have benefited through
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
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
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
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.