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Record W2035466445 · doi:10.1118/1.3476142

Poster — Thur Eve — 37: Incorporation of K‐Edge Materials into Dual‐Energy X‐Ray Imaging Theory

2010· article· en· W2035466445 on OpenAlexaff
Karl Landheer, PC Johns

Bibliographic record

VenueMedical Physics · 2010
Typearticle
Languageen
FieldEngineering
TopicAdvanced X-ray and CT Imaging
Canadian institutionsUniversity of OttawaCarleton University
Fundersnot available
KeywordsDiscontinuity (linguistics)PhysicsProjection (relational algebra)Mathematical analysisMathematicsAlgorithm

Abstract

fetched live from OpenAlex

Dual‐energy x‐ray imaging is capable of enhancing the conspicuity of materials by removing extraneous contrast. Classic dual‐energy theory, however, does not encompass materials which have a K edge in the diagnostic energy range, such as iodine contrast agent. We attempt to extend dual‐energy theory to incorporate all materials. In the first approach, a third basis material is introduced to account for the discontinuity. The transmission of a human torso consisting of muscle, adipose and iodine can be represented by equivalent thicknesses of three basis materials chosen to be Lucite, aluminum and iodine. Material look‐alike unit vectors in the Lucite, aluminum and iodine space give the direction for projecting patient data to remove contrast between any two pairs of materials. This approach fails, however, if a contrast agent different from that used as a basis material is present, such as barium. A more general extension of dual‐energy theory would accommodate different K edges. In the second approach, a K‐edge material is represented by two basis materials and a Heaviside function shifted to the K edge and scaled to give the jump ratio. The scale factor is a slowly varying function of the energy shift: the jump ratio is 5.58 for iodine (Z=53) and 5.23 for barium (Z=56). This makes it possible to describe any material by three parameters. The next step will be to link the two disjoint approaches to obtain a general extension of dual‐energy theory, of which the current theory is a projection into the two‐basis plane.

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 score0.256
Threshold uncertainty score0.554

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 head0.004
GPT teacher head0.216
Teacher spread0.212 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

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