Absolute Electrical Impedance Tomography and Spectroscopy (aEITS) is a non-intrusive imaging technique, that reconstructs images based on estimates of the absolute internal impedance distribution of an object. However, without the availability of a reference frame, it suffers from poor image quality when general assumptions are used to form the prior information about the object. This problem is intensified when selecting a multiplexing technique that introduces significant data inconsistencies. Recent attempts to solve this problem are to use data from previous empirical studies that acquired scans from Magnetic Resonance Imaging (MRI). Another approach is to use statistical methods to estimate the boundaries of the expected internal domains of the object. These approaches have shown an improvement in the reconstructed images, but either rely on data from other imaging modalities or continue to use a reference frame taken at an earlier time. Therefore, this is a non-trivial problem. In this thesis, the concept of Orthogonal Chirp Division Multiplexed aEITS (OCDM-aEITS) is introduced as an alternative multiplexing technique. OCDM-aEITS allows the simultaneous application of orthogonal wideband chirp current waveforms at all stimulation electrodes, while measuring the resultant boundary potentials. Given a single wideband measurement frame, a reference set, prior information, and several absolute images can be reconstructed. Consequently, there no longer is a need to acquire reference data, from an earlier time, or prior information from other imaging modalities. Furthermore, OCDM-aEITS overcomes some of the data inconsistencies from other multiplexing techniques (such as the data inconsistencies caused by sequential stimulation or spikes from fast pseudorandom pulse stimulation), while reconstructing images with comparable quality to those in the related literature. The experimental results from this thesis (acquired from the reconstructed images of a phantom test tank containing biological specimen), achieved an average position and size error of 3.88 % and 2.49 %, respectively.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/35574 |
| Date | 25 January 2022 |
| Creators | America, Ezra Luke |
| Contributors | Tsoeu, Mohohlo |
| Publisher | Faculty of Engineering and the Built Environment, Department of Electrical Engineering |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Doctoral Thesis, Doctoral, PhD |
| Format | application/pdf |
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