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Record W4386275897 · doi:10.1109/tmi.2023.3309967

Omnidirectional Monolithic Marker for Intra-Operative MR-Based Positional Sensing in Closed MRI

2023· article· en· W4386275897 on OpenAlexaff
Chim‐Lee Cheung, Mengjie Wu, Ge Fang, Justin Ho, Liyuan Liang, Kel Vin Tan, Fa‐Hsuan Lin, Hing‐Chiu Chang, Ka‐Wai Kwok

Bibliographic record

VenueIEEE Transactions on Medical Imaging · 2023
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of Toronto
FundersInnovation and Technology CommissionResearch Grants Council, University Grants Committee
KeywordsScannerMagnetic resonance imagingRadio frequencyComputer sciencePhysicsOpticsMedicineRadiology

Abstract

fetched live from OpenAlex

We present a design of an inductively coupled radio frequency (ICRF) marker for magnetic resonance (MR)-based positional tracking, enabling the robust increase of tracking signal at all scanning orientations in quadrature-excited closed MR imaging (MRI). The marker employs three curved resonant circuits fully covering a cylindrical surface that encloses the signal source. Each resonant circuit is a planar spiral inductor with parallel plate capacitors fabricated monolithically on flexible printed circuit board (FPC) and bent to achieve the curved structure. Size of the constructed marker is Ø3-mm ×5 -mm with quality factor > 22, and its tracking performance was validated with 1.5 T MRI scanner. As result, the marker remains as a high positive contrast spot under 360° rotations in 3 axes. The marker can be accurately localized with a maximum error of 0.56 mm under a displacement of 56 mm from the isocenter, along with an inherent standard deviation of 0.1-mm. Accrediting to the high image contrast, the presented marker enables automatic and real-time tracking in 3D without dependency on its orientation with respect to the MRI scanner receive coil. In combination with its small form-factor, the presented marker would facilitate robust and wireless MR-based tracking for intervention and clinical diagnosis. This method targets applications that can involve rotational changes in all axes (X-Y-Z).

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.912
Threshold uncertainty score0.627

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.348
Teacher spread0.330 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations5
Published2023
Admission routes1
Has abstractyes

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