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Record W2758371045 · doi:10.5114/aic.2017.70201

3D image fusion for live guidance of stent implantation in aortic coarctation – magnetic resonance imaging and computed tomography image overlay enhances interventional technique

2017· article· en· W2758371045 on OpenAlexaboutno aff
Sebastian Góreczny, Paweł Dryżek, Tomasz Moszura, Titus Kühne, Felix Berger, Stephan Schubert

Bibliographic record

VenueAdvances in Interventional Cardiology · 2017
Typearticle
Languageen
FieldMedicine
TopicRenal and Vascular Pathologies
Canadian institutionsnot available
Fundersnot available
KeywordsMagnetic resonance imagingMedicineImage fusionStentComputed tomographyRadiologyInterventional cardiologyNuclear medicineSurgeryArtificial intelligenceImage (mathematics)Computer science

Abstract

fetched live from OpenAlex

ENWEndNote BIBJabRef, Mendeley RISPapers, Reference Manager, RefWorks, Zotero AMA Goreczny S, Dryzek P, Moszura T, Kühne T, Berger F, Schubert S. 3D image fusion for live guidance of stent implantation in aortic coarctation – magnetic resonance imaging and computed tomography image overlay enhances interventional technique. Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej. 2017;13(3):269-272. doi:10.5114/aic.2017.70201. APA Goreczny, S., Dryzek, P., Moszura, T., Kühne, T., Berger, F., & Schubert, S. (2017). 3D image fusion for live guidance of stent implantation in aortic coarctation – magnetic resonance imaging and computed tomography image overlay enhances interventional technique. Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej, 13(3), 269-272. https://doi.org/10.5114/aic.2017.70201 Chicago Goreczny, Sebastian, Pawel Dryzek, Tomasz Moszura, Titus Kühne, Felix Berger, and Stephan Schubert. 2017. "3D image fusion for live guidance of stent implantation in aortic coarctation – magnetic resonance imaging and computed tomography image overlay enhances interventional technique". Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej 13 (3): 269-272. doi:10.5114/aic.2017.70201. Harvard Goreczny, S., Dryzek, P., Moszura, T., Kühne, T., Berger, F., and Schubert, S. (2017). 3D image fusion for live guidance of stent implantation in aortic coarctation – magnetic resonance imaging and computed tomography image overlay enhances interventional technique. Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej, 13(3), pp.269-272. https://doi.org/10.5114/aic.2017.70201 MLA Goreczny, Sebastian et al. "3D image fusion for live guidance of stent implantation in aortic coarctation – magnetic resonance imaging and computed tomography image overlay enhances interventional technique." Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej, vol. 13, no. 3, 2017, pp. 269-272. doi:10.5114/aic.2017.70201. Vancouver Goreczny S, Dryzek P, Moszura T, Kühne T, Berger F, Schubert S. 3D image fusion for live guidance of stent implantation in aortic coarctation – magnetic resonance imaging and computed tomography image overlay enhances interventional technique. Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej. 2017;13(3):269-272. doi:10.5114/aic.2017.70201.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.007

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 head0.013
GPT teacher head0.331
Teacher spread0.318 · 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 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

Citations14
Published2017
Admission routes1
Has abstractyes

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