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Record W3214479709 · doi:10.1063/5.0055900

Development and assessment of an x-ray tube-based multi-beam x-ray scatter projection imaging system

2021· article· en· W3214479709 on OpenAlexafffund
Christopher Dydula, Paul C. Johns

Bibliographic record

VenueReview of Scientific Instruments · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvanced X-ray and CT Imaging
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOpticsPhysicsPencil (optics)DetectorX-ray tubeSynchrotronPixelData acquisitionProjection (relational algebra)Computer science

Abstract

fetched live from OpenAlex

Coherent scatter x-ray imaging systems are sensitive to material structure and chemical composition, and generate soft-material images with contrast superior to conventional transmission x-ray imaging. For practicality in medical or security applications, the image data acquisition time should be <10 min. Our approach is a multi-beam projection imaging design. Previously, as a development stage, we implemented a synchrotron-based system with five coplanar pencil beams and continuous motion of the object. In the work reported here, we developed a more practical coherent scatter projection imaging system using a conventional x-ray tube source. The object is irradiated by an array of up to three rows by five columns of pencil beams, and motorized stages translate the object through the beams for step-and-shoot acquisition. For the same tube loading, broad spectrum beams, such as 110 kVp filtered with 2.25 mm Al, were found to provide a higher signal-difference-to-noise ratio between soft materials in scatter images than lower kVp, more heavily filtered beams that have a narrower, lower intensity spectrum. The shortest acquisition time for a 6.0 × 10.0 cm2 object with 6000 pixels was 8.8 min. The width of a sharp edge in the scatter image was consistent with the pencil beam diameter. Contrast-detail performance was similar to our synchrotron-based system. In this first x-ray tube-based system, for simplicity, the transmitted x rays are measured through attenuators using the same flat-panel detector that measures scattered x rays. As a result, the primary image quality was reduced.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.794
Threshold uncertainty score0.708

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.018
GPT teacher head0.281
Teacher spread0.263 · 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 designOther design
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

Citations4
Published2021
Admission routes2
Has abstractyes

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