MétaCan
Menu
Back to cohort
Record W2171833203 · doi:10.1120/jacmp.v12i4.3641

Antiscatter grid use in pediatric digital tomosynthesis imaging

2011· article· en· W2171833203 on OpenAlexaff
Jenna M. King, Idris A. Elbakri, Martin H. Reed

Bibliographic record

VenueJournal of Applied Clinical Medical Physics · 2011
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsChildren's Hospital of WinnipegCancerCare Manitoba
FundersGE Healthcare
KeywordsTomosynthesisImage qualityGridRadiographyMedical physicsComputer scienceDigital radiographyNuclear medicineArtificial intelligenceMedicineRadiologyImage (mathematics)MammographyMathematics

Abstract

fetched live from OpenAlex

The objective of this study was to assess the effect of antiscatter grid use on tomosynthesis image quality. We performed an observer study that rated the image quality of digital tomosynthesis scout radiographs and slice images of a Leeds TO.20 contrast-detail test object embedded in acrylic with and without a grid. We considered 10, 15, 20 and 25 cm of acrylic to represent the wide range of patient thicknesses encountered in pediatric imaging. We also acquired and rated images without a grid at an increased patient dose. The readers counted the total number of visible details in each image as a measure of relative image quality. We observed that the antiscatter grid improves tomosynthesis image quality compared to the grid-out case, which received image quality scores similar to grid-in radiography. Our results suggest that, in order to achieve the best image quality in exchange for the increase in patient dose, it may often be appropriate to include an antiscatter grid for pediatric tomosynthesis imaging, particularly if the patient thickness is greater than 10 cm.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.234
Threshold uncertainty score0.463

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
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 head0.058
GPT teacher head0.326
Teacher spread0.268 · 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 designObservational
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
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Applied Clinical Medical PhysicsSame topicRadiation Dose and ImagingFrench-language works237,207