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Record W7019873052

INVESTIGATIONS ON ASPECTS OF 1.5D TRASE MRI

2024· dissertation· en· W7019873052 on OpenAlexfundaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2024
Typedissertation
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Space Agency
KeywordsMagnetic resonance imagingReal-time MRIk-spaceImage qualityPopulationInterventional magnetic resonance imagingMedical imagingElectromagnetic coil
DOInot available

Abstract

fetched live from OpenAlex

Magnetic Resonance Imaging (MRI) was a technological breakthrough in the 1980s that provided high clinical value due to its superior soft tissue contrast relative to X-ray Computed Tomography (CT). Low field MRI, then and now, provides clinically useful image quality and contrast. Here, low field refers to magnetic fields of less than 1 Tesla. The aim of the current worldwide interest in low field MRI is to lower the cost of MRI equipment, with a reduced footprint, to make MRI accessible to a broader population of patients and users. TRansmit Array Spatial Encoding (TRASE) MRI is a gradient-free low field MRI technology in which spatial phase variation in the transmitted radio frequency (RF) magnetic field, B1, is used to encode spatial information into the MRI’s Nuclear Magnetic Resonance (NMR) signal, instead of using the switched gradient magnetic fields that clinical MRIs now use. At the Space MRI Lab at University of Saskatchewan, the focus has been on developing TRASE MRI for space applications. Monitoring astronauts’ health during space missions is a challenging but important issue. MRI imaging using gradient-free, portable TRASE MRI instruments, is a promising non-invasive approach for use in outer space for research and diagnosis purposes. The Owl MRI, a wrist size TRASE MRI prototype, has been developed and used in the Space MRI Lab. The Owl MRI, modified from its original configuration, was fitted with a twisted solenoid RF transmit coil set for 1D TRASE imaging and was used to verify the design of the Merlin MRI, a Canadian Space Agency (CSA) funded ankle-size MRI that was tested on National Research Council’s Falcon 20 jet in April 2021 during a parabolic flight campaign giving zero-gravity. To develop the Owl MRI beyond a test bed for the Merlin MRI to a fully functional MRI on its own, it was setup to image using a design we designate as 1.5D TRASE MRI. This MRI design achieves 2D image encoding in one direction with the TRASE technique and in the other direction with a built-in fixed magnetic field gradient in the Owl MRI’s Halbach magnet. TRASE MRI is a new technology that still has some unknown aspects. One of the most important and unstudied aspects of TRASE MRI is its image contrast, which still needs to be investigated in detail, and was the original motivation behind the direction of this thesis. In line with this goal and the general development of the 1.5D TRASE MRI design, some projects were accomplished for the Owl MRI’s hardware and software development, and are reported in this thesis. FORTRAN-based Bloch equation simulation software was written for simulating the TRASE images acquired from the Owl MRI. Such software is needed in order to simulate TRASE images for any desired RF pulse sequence (and phantom) choice for the ultimate purpose of TRASE contrast studies. These simulated images then can be compared with image from actual TRASE imaging experiments performed on the Owl MRI. Here the software was developed to the point where image contrast could be modelled. Comparing the simulations to real data remained a future project, as the Owl MRI was not generating images at the time of this work. Some work on the Owl MRI’s hardware was also needed, to develop and improve it, and to prepare it for real contrast experiments, and that work was also accomplished as a part of the work of this thesis. The hardware work included the development of a remote tuning circuit and 3D printed imaging phantoms. More time and comprehensive research is required to understand and characterize TRASE image contrast via performing simulation, phantom, and in vivo studies. The work in this thesis lays out some initial work in that direction.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.011
GPT teacher head0.215
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

Explore more

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