Biomedical Engineering - Theses
Permanent URI for this collection
Search Results
1 - 1 of 1
-
ItemLocalisation of the Epileptogenic Zone from Interictal State MEG Data of Focal Epilepsy Patients( 2020)Over twenty million people in the world have drug refractory epilepsy. Their seizures cannot be adequately controlled by medication. Epilepsy surgery can remove or alter abnormal brain areas where seizures start, which is the only way to cure epilepsy and can be an effective treatment for drug refractory epilepsy patients. Accurate localisation of the epileptogenic zone (EZ) is crucially important to achieve seizure freedom after surgery. Magnetoencephalography (MEG) is a non-invasive brain functional imaging technique with superb temporal resolution. Clinically, neurophysiologists visually annotate interictal spikes in MEG recordings and apply localisation methods using averaged spikes. The manual annotation of spikes can be very time consuming for neurophysiologists. The aim of this thesis is to develop automatic methods to localise the epileptogenic zone using interictal state MEG recording for focal epilepsy patients. This thesis comprises three research objectives to achieve this goal. First, investigate localisation performance of kurtosis beamforming with various source selection approaches; the use of a 1 second sliding window for calculating kurtosis is shown to deliver the best performance relative to the other measures considered. Second, develop a method to detect interictal spikes automatically on virtual sensors (VSs) that are reconstructed using beamforming; the method based on feature extraction and machine learning delivers similar performance to labels by expert raters. Third, explore spatial distribution of interictal spikes across VSs and associate spike frequencies with EZs and surgical outcomes; the method is promising for localising the EZ at the lobe level. Potential future research is discussed based on these outcomes.