GTA funded – Improved minimisation of ghosting effects in MRI scanner images using an advanced computational modelling tool for accurate prediction of magneto-mechanical vibrations

Project Highlights

1. Real world impact in medical imaging by the development of tools required by industry.
2. Interdisciplinary research in mathematics, engineering, and computer science industrial project
3. Building on an existing strong collaboration with Swansea University and Siemens Healthineers.

Project

Siemens Healthineers are a global leading company in the manufacture of MRI magnets. A key challenge for the company is the generation of ghosting artefacts that arise as part of the imaging process. These artefacts present challenges for medical professional attempting to draw diagnoses from the images. The ghosting artefacts arise due to the strong uniform magnetic field across the bore of the magnet being disturbed by eddy currents and mechanical vibrations of the conducting components of the scanner. Current processes to remove the effects are based on post-processing the images, but with the move towards more sustainable magnet designs, predicting the field perturbations and understanding how to account for them has become very challenging. The aim of this PhD is to develop a computational tool for predicting field inhomogeneities across the bore of the MRI imaging region and to understand how this can be used as part of the imaging process to minimise ghosting. The objectives are:

1.      To gain a good physical understanding of the physical engineering processes in the design and build of MRI scanners.

2.      To understand the suite of current computational tools developed by Ledger and Gil to predict magneto-mechanical coupling in MRI scanners [1] and to extend this software to predict complex situations in 3D and apply reduced order models for computational efficiency [2].

3.      To work effectively with software libraries and to build on existing software bases that lead to tools that can be used by industry.

4.      To gain familiarity with current techniques used for removing ghosting effects and how these could benefit from the additional insights provided by an accurate prediction of the field inhomogeneities across the bore of the MRI imaging region.

The student will have the opportunity to collaborate with the teams of computational engineering researchers at the Zienkiwicz Institute for Modelling and AI, Swansea University and with the industrial supervisor at Siemens Heathineers Magnet Technology.

Project enquiries to Professor Paul Ledger p.d.ledger28@gmail.com

General enquiries cmspgr@le.ac.uk

How to Apply

Please refer to the application advice and use the application link on our web page

https://le.ac.uk/study/research-degrees/funded-opportunities/maths-gta