MétaCan
Menu
Back to cohort
Record W2017387129 · doi:10.1088/0031-9155/48/20/012

A three-dimensional x-ray scattering system for multi-parameter imaging of the human head

2003· article· en· W2017387129 on OpenAlexaff
Faysal El Khettabi, I. Yaar, Esam M.A. Hussein

Bibliographic record

VenuePhysics in Medicine and Biology · 2003
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsMonte Carlo methodOpticsHuman headRadiationPhysicsScatteringAttenuationPhotonImage resolutionDetectorResolution (logic)Beam (structure)Computer scienceComputational physicsMathematicsArtificial intelligenceAbsorption (acoustics)

Abstract

fetched live from OpenAlex

This work examines the suitability of a non-rotating one-side 3D x-ray scatter system for imaging the human head. The system simultaneously produces images of the x-ray attenuation coefficients at two photon energies, as well as an image of the electron density. The system relies on measuring the scattered radiation at two directions orthogonal to an incident beam that scans the object from one side, in addition to the traditionally recorded transmitted radiation. Algorithms for this multi-parameter imaging process are presented, and their numerical viability is demonstrated, using both idealized detector responses and those independently estimated from Monte Carlo simulations. The absorbed radiation dose is also calculated, and was shown to be about one quarter of that of conventional CT systems, for 5 mm spatial-resolution images. The introduced system can therefore be useful in radiotherapy planning, and in post-treatment imaging.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.224
GPT teacher head0.432
Teacher spread0.208 · 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

Citations6
Published2003
Admission routes1
Has abstractyes

Explore more

Same venuePhysics in Medicine and BiologySame topicMedical Imaging Techniques and ApplicationsFrench-language works237,207