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Vacancies at CMIC
PhD studentship on modelling and compensating for respiratory motion during MR imaging
Supervisors: Jamie McClelland, David Atkinson, Ricky Sharma
In recent years there have been a number of new and exciting MR imaging techniques developed. These include methods that can produce highly detailed scans of the patient’s anatomy, as well as methods that can probe the microstructure of tumours and other tissue non-invasively, such as VERDICT-MRI being developed at UCL. These methods are already showing great promise for diagnosing, staging, and planning treatments for some cancer sites, and have the potential to provide bio-markers to monitor disease progression and the effectiveness of treatment. However, their use in organs that move with respiration has so far been limited, as the motion can degrade the scans and cause artefacts, and reduces the clinically useful information that can be derived from them.
Computational models of the respiratory motion can potentially be used to compensate for the motion during the reconstruction of the MR images. However, generating sufficiently accurate models of the motion has so far proved challenging, as previous methods have required good quality 3D images in order to model the 3D motion, and such images cannot be acquired fast enough to capture the respiratory motion. A new general purpose motion modelling framework has recently been developed at UCL that can model the 3D motion directly from ‘partial’ or ‘unreconstructed’ imaging data, such as individual 2D slices, or raw k-space data. Motion compensated image reconstruction can also be incorporated into this framework, so that both the motion model and the ‘motion-free’ image can be recovered from the unreconstructed imaging data. This framework has already shown great promise for use with multi-slice MR data, and the potential to work directly on raw k-space data.
This PhD studentship will further develop and tailor the motion modelling framework to work with MR data, and utilise the framework to compensate for respiratory motion during MR acquisitions. This project will provide opportunities to explore both the theoretical and applied aspects of the research, including:
· Applying the motion modelling framework directly to k-space data
· Incorporating improved image registration techniques (e.g. to handle sliding motion)
· Exploring different image reconstruction algorithms
· Simultaneously optimising the motion model and image reconstruction
· Using the framework to correct for respiratory motion in a variety of real MR scans
· Using the motion corrected scans for planning and monitoring radiotherapy treatment
This studentship will be based in the Centre for Doctoral Training in Medical Imaging and the Centre for Medical Image Computing at UCL, but will involve strong collaborations with Centre for Medical Imaging and the Cancer Institute at UCL, and the Radiology and Radiotherapy departments at UCH.
The studentship is offered as an MRes + PhD and is fully funded for 4 years (tax free stipend of £16,851 per year, plus full fees paid). This studentship is available to applicants from the UK and those from the EU who have been living in the UK for 3 or more years. For full eligibility details see: https://www.epsrc.ac.uk/skills/students/help/eligibility/. The start date for the studentship is October 2017.
If you have any questions or would like more information please email Dr Jamie McClelland: email@example.com
To apply for the position please complete an online application here. Closing date: 13th April 2017
Page last modified on 10 apr 17 13:47