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Record W4248520558 · doi:10.32920/ryerson.14653425

A Simulation of a Novel High Quantum Efficiency Scintillating Fiber Detector with Anti-scatter Properties for Megavoltage X-Ray Imaging

2021· preprint· en· W4248520558 on OpenAlexafffund
James M.D. Day

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicDigital Radiography and Breast Imaging
Canadian institutionsToronto Metropolitan UniversityUniversity of Regina
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOpticsDetectorImage resolutionSquare (algebra)Monte Carlo methodMaterials scienceResolution (logic)Linear particle acceleratorRangingBeam (structure)PhysicsComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

To further develop a MV x-ray portal imaging device with high detection efficiency and adequate spatial resolution for image guided radiation therapy, the experimental results for a prototype detector were matched using Monte-Carlo software to then improve upon the design. The simulation and experiment were carried out using a 6 MV beam from a linear accelerator machine. An adequate match was obtained with the spatial resolution matching up to a MTF value of 0.2 and then diverging and the total signal registered in the central fiber was matched for field sizes ranging from 3 cm by 3 cm to 20 cm by 20 cm for 5 cm, 15 cm and 25 cm air gaps within 3%. The design was altered from a hexagonal array of round double cladded fibers to a square array of single cladded square fibers. The spatial resolution was improved from 0.242 lp mm-1 to 0.359 lp mm-1 at an MTF value of 0.5 from the original design to a square array of square fibers 0.5 mm wide separated by 0.25 mm of lead foil. With further optimization of the detector design it may be possible to increase spatial resolution for MV x-ray imaging while maintaining an adequate detection efficiency.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.226
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.025
GPT teacher head0.262
Teacher spread0.238 · 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.

Study designSimulation or modeling
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
Published2021
Admission routes2
Has abstractyes

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