Interventional magnetic resonance imaging (iMRI) is being increasingly used for performing imageguided
neurosurgical procedures. Intermittent imaging through iMRI can help a neurosurgeon visualise
the target and eloquent brain areas during neurosurgery and lead to better patient outcome. MRI plays
an important role in planning and performing neurosurgical procedures because it can provide highresolution
anatomical images that can be used to discriminate between healthy and diseased tissue, as
well as identify location and extent of functional areas. This is of significant clinical utility as it helps
the surgeons maximise target resection and avoid damage to functionally important brain areas.
There is clinical interest in propagating the pre-operative surgical information to the intra-operative
image space as this allows the surgeons to utilise the pre-operatively generated surgical plans during
surgery. The current state of the art neuronavigation systems achieve this by performing rigid registration
of pre-operative and intra-operative images. As the brain undergoes non-linear deformations after
craniotomy (brain shift), the rigidly registered pre-operative images do not accurately align anymore
with the intra-operative images acquired during surgery. This limits the accuracy of these neuronavigation
systems and hampers the surgeonβs ability to perform more aggressive interventions. In addition,
intra-operative images are typically of lower quality with susceptibility artefacts inducing severe geometric
and intensity distortions around areas of resection in echo planar MRI images, significantly reducing
their utility in the intraoperative setting.
This thesis focuses on development of novel methods for an image processing workflow that aims
to maximise the utility of iMRI in neurosurgery. I present a fast, non-rigid registration algorithm that
can leverage information from both structural and diffusion weighted MRI images to localise target
lesions and a critical white matter tract, the optic radiation, during surgical management of temporal
lobe epilepsy. A novel method for correcting susceptibility artefacts in echo planar MRI images is also
developed, which combines fieldmap and image registration based correction techniques. The work
developed in this thesis has been validated and successfully integrated into the surgical workflow at the
National Hospital for Neurology and Neurosurgery in London and is being clinically used to inform
surgical decisions