Layout Image

Professor Simon Arridge

Layout Image

Professor Simon Arridge

Research

 

Simon Arridge's research interests primarily lie in the area of tomography in medical imaging, specifically the application of inverse problem techniques to image reconstruction.  Inverse problems can be linear or non-linear and either well posed or ill-posed.  Ill-posed inverse problems usually require regularisation techniques which can be placed within the general frame work of Bayesian estimation, where the assumed prior distribution of the image under consideration plays the role of a penalty term in a constrained or unconstrained posterior probability optimisation.

 A topic of research for the last 20 years has been the development of optical tomography an imaging modality detecting the contrast of absorption and scattering of light in the visible and near-infrared region of the spectrum. In this wavelength range photons are so strongly scattered that they are quite well described by a diffusion or randomwalk process in which the density of photons follows a Gaussian distribution with respect to distance from a source. The inverse problem for this imaging modality is non-linear and ill-posed. Significant improvements in image quality can be gained by using time-of-flight measurements using photon-counting detectors. This technique has been pioneered in the Medical Physics department where I did my PhD, and is one of the co-hosts of CMIC. Optical tomography extends to fluorescence optical tomography in which the  contrast is the stimulated emission of light at another wavelength, discriminated from the background by spectral filtering, and photoacoustic tomography where the contrast is stimulated emission of ultrasound waves, which do not suffer significantly from attenuation.

Other research topics that use similar methods are fast cardiac MRI, digital tomosynthesis, electro cardio physiology, and nuclear medicine (SPECT and PET). As well as the use of generic priors such as distribution of edges, I am currently investigating the use of cross-modality priors which involves other topics such as information-theoretic measures, probabilistic atlases, and image registration.

 Contact Details:

University College London
Centre for Medical Image Computing
3rd Floor
Engineering Front Building
Malet Place
London WC1E 6BT
United Kingdom

Office: 3.06
Tel: +44 (0)20 7679 0221 (Direct Dial)
Internal: 33714
Fax: +44 (0)20 7387 1397
Email: s.arridge@cs.ucl.ac.uk

Layout Image
Layout Image Layout Image

Centre for Medical Image Computing - University College London - Gower Street - London - WC1E 6BT - Telephone: +44 (0)20 7679 0221 - Copyright © 1999-2009 UCL. Disclaimer | Accessibility | Privacy | UCL Search | UCL-CS Help