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: email@example.com; 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.