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Record W2128684771 · doi:10.1109/tns.2004.829600

A nonrotating multiparameter 3-D X-ray imaging system-Part I: modeling and reconstruction

2004· article· en· W2128684771 on OpenAlexaff
Faysal El Khettabi, Esam M.A. Hussein, Hassan A. Jama

Bibliographic record

VenueIEEE Transactions on Nuclear Science · 2004
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsPhysicsIterative reconstructionTomographic reconstructionOpticsAttenuationCompton scatteringVoxelRotation (mathematics)TomographyRadiationPerpendicularBeam (structure)Projection (relational algebra)Computational physicsComputer scienceScatteringComputer visionGeometryAlgorithmMathematics

Abstract

fetched live from OpenAlex

A 3-D X-ray imaging system that eliminates the rotation process associated with tomographic systems is introduced. The system relies on measuring the intensity of Compton scattered radiation in two directions mutually perpendicular to an incident beam that rectilinearly scans the object. These measurements, along with transmission measurements obtained from one-side exposure of the object are utilized to reconstruct 3-D images of three physical parameters: two attenuation coefficients corresponding to the incident and scattered energies, and the electron-density in each voxel. This part of the paper addresses the theoretical and physical aspects associated with the image reconstruction process, and presents examples of images reconstructed from experimental results.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.020
GPT teacher head0.277
Teacher spread0.256 · 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 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

Citations7
Published2004
Admission routes1
Has abstractyes

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