Near-field microwave tomography systems and the use of a scatterer probe technique
Bibliographic record
Abstract
This dissertation presents the contributions and the research conducted in developing and implementing Microwave Tomography (MWT) systems. MWT is an imaging modality which aims to interrogate an object of interest by microwave energy, and quantitatively “find” the interior spatial distribution of its dielectric properties using field measurements taken outside the object. Due to the inherent non-linearity of the MWT problem, a substantial amount of electromagnetic scattering data is required to ensure a robust inversion and quantitatively accurate imaging results. This research benefits a variety of applications including biomedical imaging, industrial non-destructive testing, and security applications. Developing a MWT system, requires many critical components including the bandwidth and polarization purity of the collected fields as well as calibration of the fields scattered by the object of interest. Two generations of MWT systems were designed, implemented, calibrated and tested at the University of Manitoba (UM). These systems aim different approaches for near-field measurements which are referred to as the direct and indirect methods. With regard to the antenna design, a novel methodology applicable to broadband planar antennas is introduced. This technique is based on a combination of field modelling, herein, the finite element method and transmission line modelling. In the first generation of the UM MWT systems, a suitable antenna system was utilized. The system under study was a prototype, where twenty-four co-resident antennas encircle the object of interest to directly measure the fields. In the second generation of the UM MWT systems, the feasibility of using a novel technique to indirectly measure the fields by a secondary array of near-field scatterer probes was studied. The technique is based on the Modulated Scatterer Technique (MST). In this system, antennas are called ``collectors", since the role of antennas are changed to collecting probes' scattered fields. A number of PIN diodes were utilized to activate the probes. Finally, the capability of the probe system was investigated and its performance with the previously constructed tomography systems was compared. Various dielectric phantoms were utilized to test the accuracy of the systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".