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Record W2091317800 · doi:10.1088/0031-9155/52/8/009

Physical characterization of a high-resolution CCD detector for mammography

2007· article· en· W2091317800 on OpenAlexaff
I Elbakri, Mike M. Tesic, Quanren Xiong

Bibliographic record

VenuePhysics in Medicine and Biology · 2007
Typearticle
Languageen
FieldMedicine
TopicDigital Radiography and Breast Imaging
Canadian institutionsCancerCare Manitoba
Fundersnot available
KeywordsDetective quantum efficiencyDetectorOpticsOptical transfer functionPhysicsNoise (video)Materials scienceNoise powerImage qualityPower (physics)Computer science

Abstract

fetched live from OpenAlex

The physical characteristics of charge-coupled device (CCD) mammography detector with 16-bit dynamic range and 27 microm detector element size were investigated. The detector, with an active area of 1 cm x 20 cm is suitable for slot-scanning systems. We evaluated the detector resolution by measuring the modulation transfer function (MTF) using a tilted edge. We also measured the noise power spectra (NPS) and detective quantum efficiency (DQE) using tungsten spectra filtered with 3 mm Al. We carried out measurements in two modes of operation: the frame mode where the detector is stationary and the scan mode where the detector operates in a slot-scanning configuration. The specific beam qualities and exposure ranges employed were 30 kVp, HVL 1.4 mm Al, 1.24 microC kg(-1) to 12.44 microC kg(-1), and 40 kVp, HVL 2.1 mm Al and 3.26 microC kg(-1) to 16.64 microC kg(-1). The product of the normalized noise power spectrum and exposure was also computed to evaluate the quantum limited characteristic of the detector. The detector MTF was 12% at 15 lp mm(-1). The product of the noise power spectra and exposure was independent of exposure level, indicating a quantum limited detector. The DQE in the scan and frame modes near zero frequency was 40% and 60%, respectively. Our results show that the slot-scanning configuration was less efficient than the performance capabilities of the detector. This detector is comparable to other digital mammography sensors evaluated in the literature.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.777
Threshold uncertainty score0.271

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 head0.073
GPT teacher head0.350
Teacher spread0.277 · 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

Citations3
Published2007
Admission routes1
Has abstractyes

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