Image Reconstruction

Imaging has revolutionised the role of data acquisition within healthcare, allowing non-invasive visualisation, both qualitatively and quantitatively, of a vast range of clinically critical parameters. Whereas direct imaging allows for the capture of data across the electromagnetic and acoustic spectra, in many cases continuously and in real-time, indirect imaging incorporates also a reconstruction step that allows the clinician to infer many other physical quantities through the solution of an inverse problem based for example on a physical or statistical model of the data acquisition process. This theme addresses the reconstruction task at the intersection of advanced skills in mathematics, natural sciences, computing, statistics, and engineering. The UK has an outstanding track record of invention in imaging and measurement systems, for example the early development of X-ray CT and Magnetic Resonance Imaging, both awarded Nobel prizes. Emerging hybrid medical imaging methods such as photoacoustic tomography and magnetic resonance impedance tomography are at a phase of rapid technological and mathematical development, and improvements of existing methods including fast CT, MRI for lung dynamics and limited data dental CT will continue to ensure such success.The demand for a trained cohort of experts with these diverse skills is constant and high, both nationally and internationally.

Theme Leader: Prof. Simon Arridge

Page last modified on 01 dec 13 21:35