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Record W2809776285 · doi:10.1002/mp.13073

Performance characterization of an integrated cone‐beam <scp>CT</scp> system for dedicated gamma radiosurgery

2018· article· en· W2809776285 on OpenAlexaff
Arman Sarfehnia, Mark Ruschin, Brige Chugh, Collins Yeboah, Nathan Becker, Young‐Bin Cho, Young Lee

Bibliographic record

VenueMedical Physics · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsPrincess Margaret Cancer CentreHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsRadiosurgeryScannerComputer scienceImage qualityImage-guided radiation therapyCone beam ctTilt (camera)Medical physicsComputer visionNuclear medicineMedical imagingArtificial intelligencePhysicsMedicineRadiation therapyComputed tomographyImage (mathematics)EngineeringRadiologyMechanical engineering

Abstract

fetched live from OpenAlex

PURPOSE: Icon™. METHODS: The performance tests have been categorized into: (a) image quality and mechanical integrity; (b) image coregistration fidelity; (c) adaptive treatment delivery quality; (d) high definition motion management performance characterization; (e) software communication performance testing of the integrated cone-beam CT (CBCT) system. RESULTS: All image quality performance characterization satisfied or exceeded manufacturer specifications. The image quality and mechanical stability of the CBCT system over a 3-month period was within tolerance with negligible (<0.1°) detector tilt angle. The CBCT definition of the stereotactic space had a measured average discrepancy of 0.15-0.16 mm in x, y, and z directions. On average, the high definition motion management system performance was within 0.05 mm with a residual offset of 0.15 mm when large displacements in a given direction were taken. The adaptive treatment delivery component as measured with CBCT coregistration of daily setups against reference setup images was accurate to within 0.2°. Comprehensive end-to-end testing showed a total uncertainty of better than 0.2 mm in positioning and 0.4% in dosimetry for treatment of centrally located lesions. CONCLUSIONS: A set of system performance characterization tests spanning all aspects of the Gamma Knife Icon are presented. Overall, the system performance was in line with manufacturer specifications.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.732
Threshold uncertainty score0.711

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 head0.010
GPT teacher head0.254
Teacher spread0.244 · 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

Citations19
Published2018
Admission routes1
Has abstractyes

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