Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.296819
Title: A study of three dimensional effects in induced current impedance imaging
Author: Healey, Timothy James
Awarding Body: University of Sheffield
Current Institution: University of Sheffield
Date of Award: 1995
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Abstract:
Previous studies of the induced current impedance imaging technique have been unable to reconstruct images of three dimensional (3-D) structures. In this study the cause of the problem is identified and the reconstruction algorithm of Purvis is adapted to facilitate the correct reconstruction of images of a limited class of structures which have the form of a long cylinder. The images produced by the algorithm are improved by a data filter based on that of Barber, Brown and Avis. By consideration of the underlying field equations which govern 3-D induced current Electrical Impedance Tomography (EIT) systems, the finite element method (FEM) is used for the computation of the potential field for arbitrary conductivity distributions excited by various coil configurations. A phantom system is built to test the results of the FEM and particular attention is paid to the improvement of the instrumentation. A statistical comparison of the results of measurement and simulation is unable to detect any error in the FEM model. The FEM model is consequently used to develop the reconstruction algorithm but physical measurements are also used to test the algorithm in the presence of noise. The behaviour of the 3-D algorithm is tested for its plane selectivity showing Similar characteristics to those of injected current systems developed by other workers. A possible approach which could both reduce the volume to which the system is sensitive and generate extra measurements for the possible reconstruction of multi-layered images is investigated.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.296819  DOI: Not available
Keywords: Pattern recognition & image processing
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