Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.756002
Title: A novel framework for head imaging with Electrical Impedance Tomography
Author: Jehl, M. F.
ISNI:       0000 0004 7428 9599
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2016
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Abstract:
Electrical Impedance Tomography (EIT) is a medical imaging technology with the potential to locate focal epilepsy, monitor patients with traumatic brain injury and diagnose stroke. EIT usually images conductivity changes in time or in frequency of the applied current and measured voltages. While it is nowadays clinically used for monitoring lung ventilation, its application in head imaging is complicated by the geometry of the head, containing tissues with strongly varying conductivities. The aim of this thesis is to provide a novel framework for EIT head imaging by addressing the requirements for higher modelling accuracy throughout the imaging process. An introduction to EIT, its applications for head imaging and the two main components of EIT image reconstructions is given in chapter 2. A procedure for generating more accurate head models is presented in chapter 3 and is used to evaluate, whether subject specifc head models are required for EIT imaging. To speed up simulations of current fow through the head and the computation of the Jacobian matrix required for image reconstructions, a fast parallel forward solver is implemented and validated in chapter 4. Stability of time-diference image reconstructions with respect to electrode modelling errors is addressed in chapter 5, followed by an evaluation of modelling error impacts on multi-frequency imaging in chapter 6. The fndings of chapters 5 and 6 are fnally combined in chapter 7 to recover electrode positions in multi-frequency stroke imaging, thereby reducing image artefacts and making stroke diagnosis with EIT feasible.
Supervisor: Betcke, T. ; Holder, D. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.756002  DOI: Not available
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