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Dr Dean Barratt
2.04
Department of Medical Physics
Floor 2, Malet Place Engineering Building
London
WC1E 6BT
Appointment
  • Reader in Medical Image Computing
  • Dept of Med Phys & Biomedical Eng
  • Faculty of Engineering Science
Biography

After leaving Desborough School in Maidenhead, Berkshire, I studied Engineering and Computing Science at Oxford University, followed by Engineering and Physical Sciences in Medicine at Imperial College London, graduating with an MEng(Hons) and an MSc degree in 1994 and 1995, respectively. I was then employed as a research assistant at Charing Cross and St. Mary’s Hospitals, where I worked on research projects led by vascular surgeons and clinicians specialising in vascular disease and hypertension. During this period, I registered for a part-time PhD. I subsequently received a PhD from Imperial College in 2001 for my thesis on 3D ultrasound imaging and quantification of atherosclerotic disease in the carotid arteries 

Following a short period working as a commercial software developer, in 2002 I joined the Computational Imaging Sciences Group at Guy’s Hospital, led by Professor David Hawkes, as a post‑doctoral research fellow proceeded to work on a number of projects in the field of image‑guided interventions. The group moved to UCL in 2005 to form the UCL Centre for Medical Image Computing (CMIC). In 2006, I was awarded a five‑year Royal Academy of Engineering/EPSRC Research Fellowship  focused on developing ultrasound-based image registration techniques for guiding surgical procedures. During the fellowship, I developed novel technologies for image-guided, minimally-invasive procedures for diagnosing and treating prostate and liver cancers. In 2011, I was appointed as a Senior Lecturer in CMIC and the Department of Medical Physics& Bioengineering.



Research Summary

A central theme of my research is the development of enabling software-based technologies - in particular, image registration (i.e. alignment) techniques - that allow data from diagnostic and/or surgical planning images available before a procedure to be aligned with images obtained during the procedure to aid surgical  navigation. Much of my research in this field has focussed on developing image guidance methods that employ three-dimensional (3D) ultrasound imaging. In my early work in this area, I developed techniques for improving the guidance of neurosurgical and orthopaedic procedures by using ultrasound as a non invasive method for localising anatomical structures and developing algorithms for registering pre-operative CT and magnetic resonance (MR) images to the patient during surgery.

More recently, I have concentrated on developing registration techniques for minimally-invasive surgical procedures, particularly those involving the prostate and the liver, where ultrasound is already used routinely, for example to guide needle biopsy. Technical challenges addressed by my research 
include registering images with very different characteristics, compensating for soft-tissue motion, and meeting the clinical requirements of minimal user interaction and speed.

My research team has developed an automatic method for non-rigidly registering MR and US images of the prostate, which has applications in guiding needle biopsy and a wide range of minimally-invasive prostate cancer therapies. We have also developed robust organ motion modelling methods for use 
during high-intensity focused ultrasound (HIFU) therapy of liver cancer, and a general-purpose algorithm for deformable registration of  blood vessels and other tubular structures. Much of this research 
has drawn heavily on computational techniques for modelling variations in organ shape, soft-tissue deformation, and ultrasound image formation.

A key goal of my research has been translating image guidance technology and associated techniques into clinical practice. To this end, our prostate registration software is currently being used for tumour targeting in a number of clinical trials and we have started to develop a commercial 
device. Furthermore, our work in modelling prostate biopsy forms the the basis of clinical criteria for stratifying prostate cancer risk and is now being used to determine recommended treatment options for patients at UCLH and a number of other centres in the UK.


Teaching Summary

Since 2011 I have been the course organiser and tutor for the Medical Image Computing MSc (now one of three routes of the Physics in Engineering and Medicine MSc programme).

I teach the on following MSc courses:
Foundations of Programming for Medical Image Analysis (MPHYGB24) - Course organiser and MATLAB programming
Computing in Medicine (MPHYGB21) - Image Processing and Analysis
Ultrasound Imaging (P2 - MSc Advanced Neuroimaging)
Doppler Ultrasound Assessment of Neurovascular Disease (P1 - MSc Advanced Neuroimaging)
I also regularly provide practical 

Appointments
01-OCT-2011 Senior Lecturer Medical Physics & Bioengineering University College London, United Kingdom
Academic Background
2002 PhD Doctor of Philosophy – Medical Imaging Imperial College of Science, Technology and Medicine
1995 MSc Master of Science – Engineering and Physical Science in Medicine Imperial College of Science, Technology and Medicine
1994 MEng (Hons) Master of Engineering (Honours) – Engineering and Computing Science University of Oxford
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