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UPDATE: We are delighted to announce that EPSRC have funded our CDT for five more years under the new name EPSRC Centre for Doctoral Training in Intelligent Integrated Imaging in Healthcare (i4health).

Visit our new website at: www.ucl.ac.uk/i4health

06 Mar

New methods for improved MRI of lung diseases

Named Projects
APPLICATION CLOSING DATE: 22nd MARCH 2019

Project summary
A 4-year PhD studentship is available in the UCL Centre for Medical Image Computing (CMIC). The funding covers an annual tax free stipend (at least £17,280) and tuition fees. As the studentship is partially funded by the EPSRC the standard EPSRC eligibility criteria apply, please see EPSRC website for further details. The successful candidate will join the UCL CDT in Intelligent, Integrated Imaging in Healthcare (i4health) cohort and benefit from the activities and events organised by the centre.

Background
Lung diseases are the second most common cause of death and lead to substantial degradation of quality of life in suffers. Improved tools for diagnosing and monitoring lung disease will provide better patient characterisation and enable more appropriate treatment options to be selected. Recent work by the supervisory team has shown that new magnetic resonance imaging (MRI) methods can provide information on the structure and function of the lung and that these methods are sensitive to disease and to the impact of treatment. However, despite these developments, current lung MRI is subject to poor image quality, which limits our ability to extract detailed information.

Research Aims
This project will address some of the key current limitations of lung MRI. Breathing motion degrades image quality by causing changes in the location of important structures and introduces unwanted signals in the images. Heart pulsation leads to additional unwanted signal fluctuations. These signals will be modelled and removed from time series of MR images in order to improve the detection of detailed structures. The enhanced information content within the image time series will then be modelled to extract functional information, including lung ventilation and perfusion. These methods will be applied to existing MRI data available in conditions including lung cancer and cystic fibrosis.

Requirements
Applicants are expected to have a first degree in Physics, Computer Science or Biomedical Engineering or relevant Physical Sciences based subject passed at 2:1 level (UK system or equivalent) or above. Good working knowledge of C++ and/or Python and/or MATLAB is desirable. Some experience with medical imaging is also desirable.

To Apply
Please send a CV and Covering Letter expressing your interest to Professor Geoff Parker ucacgp1@ucl.ac.uk

APPLICATION CLOSING DATE: 22nd MARCH 2019