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Record W2052424626 · doi:10.1109/tmi.2003.816951

A hybrid breast biopsy system combining ultrasound and MRI

2003· article· en· W2052424626 on OpenAlexaff
Cameron Piron, Petrina A. Causer, Roberta A. Jong, Rene Shumak, Donald B. Plewes

Bibliographic record

VenueIEEE Transactions on Medical Imaging · 2003
Typearticle
Languageen
FieldMedicine
TopicMRI in cancer diagnosis
Canadian institutionsHealth Sciences CentreUniversity of TorontoCancer Care OntarioSunnybrook Health Science Centre
Fundersnot available
KeywordsImaging phantomBiopsyMagnetic resonance imagingUltrasoundBreast biopsyRadiologySampling (signal processing)MedicineCore biopsyComputer scienceMammographyNuclear medicineComputer visionBreast cancer

Abstract

fetched live from OpenAlex

System design and initial phantom accuracy results for a novel biopsy system integrating both magnetic resonance (MR) and ultrasound (US) imaging modalities are presented. A phantom experiment was performed to investigate the efficacy of this hybrid guidance biopsy technique in a breast tissue mimicking phantom. A comparison between MR-guided core biopsy verses MR/US-guided core biopsy of phantom targets was realized using a scoring system based on the consistency of the acquired core samples (14 gauge). It was determined that the addition of US to guide needle placement improved the accuracy from an average score of 7.4 out of 10 (MRI guidance alone), to 9.6 (MRI/US guidance) over 21 trials. The average amount of needle tip correction resulting from the additional US information was determined to be 3.7 mm. This correction value is substantial, equal to approximately one radius of the intended targets. Hybrid US/MRI guided biopsy appears to offer a simple means to ensure accurate breast tissue sampling without the need for repeat MRI scans for verification or the need for real-time imaging in open MRI geometries.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.863
Threshold uncertainty score0.877

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.265
Teacher spread0.255 · 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 designOther design
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

Citations41
Published2003
Admission routes1
Has abstractyes

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