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Record W3133400574 · doi:10.1117/12.2582225

Evaluation of edge-illumination and propagation-based x-ray phase contrast imaging methods for high resolution imaging application

2021· article· en· W3133400574 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced X-ray Imaging Techniques
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPhase-contrast imagingX-Ray Phase-Contrast ImagingContrast (vision)Image resolutionOpticsResolution (logic)Computer sciencePhase contrast microscopyPhase (matter)Enhanced Data Rates for GSM EvolutionComputer visionArtificial intelligenceMaterials sciencePhysics

Abstract

fetched live from OpenAlex

The aim of this study is to investigate and reveal the potential of employing a direct conversion amorphous selenium (a-Se) CMOS based high resolution x-ray detector in both propagation-based (PB) and edge illumination (EI) x-ray phase contrast imaging (XPCi) techniques. Both PB-XPCi and EI-XPCi modalities are evaluated through a numerical model and are compared based on their contrast, edge-enhancement, visibility, and dose efficiency characteristics. It is demonstrated how EI-XPCi configuration outperforms the PB-XPCi one considering using the same x-ray source and detector. After highlighting the strength of EI-XPCi system and reviewing today’s XPCi technologies, absorption mask grating fabrication is addressed as the main challenge to upgrade and improve EI-XPCi setups to higher resolution detectors. Mammography is considered as a case study to elucidate the importance of employing a high resolution EI-XPCi technique for microcalcification detection through numerical simulation of a breast phantom.

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.

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)0.002
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: Methods · Consensus signal: none
Teacher disagreement score0.726
Threshold uncertainty score0.570

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.021
GPT teacher head0.389
Teacher spread0.369 · 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

Quick stats

Citations7
Published2021
Admission routes1
Has abstractyes

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