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Record W1986978712 · doi:10.1118/1.2977536

Normalization of the modulation transfer function: The open‐field approach

2008· article· en· W1986978712 on OpenAlexaff
Saul N. Friedman, Ian A. Cunningham

Bibliographic record

VenueMedical Physics · 2008
Typearticle
Languageen
FieldMedicine
TopicDigital Radiography and Breast Imaging
Canadian institutionsLawson Health Research InstituteRobarts Clinical TrialsWestern University
Fundersnot available
KeywordsNormalization (sociology)Optical transfer functionSpectral leakageTransfer functionSpatial frequencyRegion of interestImage resolutionOpticsPhysicsMathematicsAlgorithmArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

The modulation transfer function (MTF) is widely used to describe the spatial resolution of x-ray imaging systems. The MTF is defined to have a zero-frequency value of unity, and it is common practice to ensure this by normalizing a measured MTF curve by the zero-frequency value. However, truncation of the line spread function (LSF) within a finite region of interest (ROI) results in spectral leakage and causes a reduction in the measured MTF zero-frequency value equal to the area of truncated LSF tails. Subsequent normalization by this value may result in inflated MTF values. We show that open-field normalization with the edge method produces accurate MTF values at all nonzero frequencies without need for further normalization by the zero-frequency value, regardless of ROI size. While both normalization techniques are equivalent for a sufficiently large ROI, a 5% inflation in MTF values was observed for a CsI-based flat-panel system when using a 10 cm ROI. Use of open-field normalization avoids potential inflation caused by zero-frequency normalization.

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: none
Teacher disagreement score0.747
Threshold uncertainty score0.127

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 head0.024
GPT teacher head0.244
Teacher spread0.219 · 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

Citations34
Published2008
Admission routes1
Has abstractyes

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