Radio Frequency Power Amplifiers Adapted For Low Field Magnetic Resonance Imaging
Bibliographic record
Abstract
Magnetic Resonance Imaging (MRI) is a reliable and established minimally invasive imaging technique that can provide diagnostically relevant information about the internal structures of the human body. While the basic design of the new MRI scanners is not much different from when they were first designed a few decades ago, finding new ways to modify these big, power-hungry, expensive and complex systems is becoming more and more essential. One of the ways of removing the restrictions that conventional MRI systems have is making them low field. This leads to lighter, smaller, simpler and less expensive MRI scanners that can potentially become portable. Once they are portable, MRI scanners can have various applications ranging from being used in emergency and operating rooms to being taken to remote areas and even outer space. The Space MRI Lab at the University of Saskatchewan focuses on building prototypes of portable MRIs for monitoring astronaut health by using TRansmit Array Spatial Encoding (TRASE). TRASE is an innovative MRI method that operates without relying on noisy, heavy and complex gradient coils. In TRASE, the spatial encoding happens based on the phase gradients of the transmit radio frequency (RF) magnetic field. \nTRASE-based MRI scanners have specific requirements. One of those requirements is RF power amplifiers (RFPAs) with high-power RF output, high duty cycle and fast switching times. These characteristics are important for achieving maximal TRASE MRI resolution. However, since no commercially available RFPA with these specifications exists, it was necessary to build RFPAs customized for TRASE applications. A class A/B Ham radio power amplifier design was modified to be more compatible with TRASE-based MRIs. As part of this thesis, two of these RFPAs were constructed at the University of Saskatchewan Space MRI Lab. The RFPAs were assembled to be used with the Merlin MRI, an ankle-sized portable MRI tested in zero-gravity which uses TRASE. Fortunately, both of the RFPAs showed expected results at the testing stage and have since been integrated with the Merlin MRI. Details of the assembly work are presented in this thesis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.083 | 0.000 |
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 teacher head, 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".