Dr.
Dean Barratt, PhD
UCL Senior Research Fellow; Royal Academy of Engineering/EPSRC Research Fellow; Honorary Research Fellow, UCL Hospitals NHS Trust
Centre for Medical Image Computing (CMIC), Room 2.20, Malet Place Engineering Building.
Email: d.barratt@ucl.ac.uk; Tel: 020 7679 0205 (#30205 internally)
My research interests
are in the use of 3D ultrasound (US) imaging for guiding medical interventions,
such as biopsy, minimally invasive surgery, and other minimally invasive
therapies.
US is already used for
realtime guidance of a number of established clinical interventions, for
example, amniocentesis. However, there
are many interventions where conventional realtime US is difficult or impossible
to apply, either because 2D US imaging is inadequate, or because the US images
themselves provide insufficient anatomical information to accurately guide the
intervention.
An alternative solution
to the guidance problem is to use one or more high-quality, pre-interventional
3D images to guide the intervention after registering these to the patient.
Such images, obtained using magnetic resonance (MR) or x-ray computer
tomography (CT) techniques, are now routinely acquired as part of the
diagnostic process for many diseases. They are also obtained specifically for
guiding some interventions, such as neurosurgery.
I am primarily
interested in developing novel image registration techniques that enable 3D US
images, acquired during an intervention, to be used to register pre-treatment
MR/CT images to the patient during an intervention. US imaging is well suited
to this purpose, as it is safe, non-invasive, inexpensive, portable, widely
available, and extremely versatile. Importantly, it also allows dense information
on organ deformation to be obtained, compensation of which is essential for
accurate guidance during some interventions. Essentially, this problem is a
“multimodal” image registration task, where the aim is to align the US images
with the MR/CT images. However, because the characteristics of US images are so
different to MR or CT images (in terms of grey-level intensity characteristics
and artefacts), in general, this is a challenging problem for which
general-purpose, automatic solutions do not currently exist.
Currently, I am working
on the following clinical applications: minimally invasive interventions for
prostate cancer (e.g. high intensity focussed ultrasound (HIFU) and
interstitial photodynamic therapy (PDT)), neurosurgery (brain tumour excision),
and orthopaedic surgery (hip replacement). I am also very interested in
minimally invasive therapies for treating liver tumours.