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Record W2583507232 · doi:10.5539/apr.v9n1p105

Effect of Backscattered Radiation on X-Ray Image Contrast

2017· article· en· W2583507232 on OpenAlexvenueno aff
Abdullah Taher Naji, Mohamad Suhaimi Jaafar, Esmail Abdo Mohammed Ali, S. K. J. Al‐Ani

Bibliographic record

VenueApplied Physics Research · 2017
Typearticle
Languageen
FieldEngineering
TopicAdvanced X-ray and CT Imaging
Canadian institutionsnot available
Fundersnot available
KeywordsDensitometerContrast (vision)Materials scienceOpticsRadiationWedge (geometry)X-rayImage contrastBackscatter (email)PhysicsComputer science

Abstract

fetched live from OpenAlex

This paper assesses the effect of backscattered radiation on X-ray image contrast by evaluating the effect of backscatter reduction on X-ray image contrast. Contrast test tool RMI Densitometer, and different types of fabricated anti backscattered grids have been utilized in this study. The measurements are recorded at different exposure parameters such as X-ray tube peak voltage (kVp), and X-rays intensities (mAs). For each exposure, the contrast of the image is evaluated by measuring the variation in optical densities for aluminium steps wedge. The results showed that the x-ray image contrast can be enhanced by decreasing the amount of backscattered radiation, also the fabricated anti backscattered grids have a remarkable effect in the improvement of X-ray image contrast according to grid’s capability in reducing backscattered radiation. In addition, the effectiveness of fabricated grids in improving image contrast depends on the grid’s material and the geometrical design, as well as the radiation exposure parameters. The image contrast enhancements increased up to 36% with the use of crossed iron steel grid which placed under the film screen combination during exposure.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.286
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.022
GPT teacher head0.350
Teacher spread0.329 · 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 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

Citations1
Published2017
Admission routes1
Has abstractyes

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