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Record W1910842482 · doi:10.1109/imtc.1998.679854

Development and evaluation of a 3D ultrasound imaging system

2002· article· en· W1910842482 on OpenAlexafffund
Aaron Fenster, Neale Cardinal, S Tong, D.B. Downey

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsWestern University
FundersMedical Research Council Canada
KeywordsUltrasound3D ultrasoundProstateUltrasound imagingConsistency (knowledge bases)Prostate cancerComputer scienceReproducibilityComputer visionMedicineMedical imagingRadiologyArtificial intelligenceMedical physicsCancerMathematics

Abstract

fetched live from OpenAlex

The use of a 3D ultrasound imaging to perform a prostate examination will overcome the limitations of conventional 2D transrectal ultrasound (TRUS) and permit the estimation of prostate and tumor volumes with greater accuracy and and consistency. In this way, the diagnosis and staging of prostate cancer can be made more accurate and less operator dependent. With a 3D ultrasound imaging system, the patient's prostate can be scanned in only a few seconds and the resulting 3D image can be later manipulated and viewed interactively on a computer, after the patient has departed, and prostate and tumor volumes can be measured with better accuracy and reproducibility. The authors developed a 3D TRUS system to image the prostate.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.046
GPT teacher head0.292
Teacher spread0.247 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2002
Admission routes2
Has abstractyes

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