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Record W2045384238 · doi:10.1118/1.4740156

Poster — Thur Eve — 48: An inexpensive and convenient phantom for quality assurance in image guidance based radiosurgery

2012· article· en· W2045384238 on OpenAlexaff
E Soisson

Bibliographic record

VenueMedical Physics · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsImaging phantomQuality assuranceRadiosurgeryComputer scienceFiducial markerImage qualityMedical imagingMedical physicsMaterials scienceComputer visionOpticsArtificial intelligencePhysicsMedicineImage (mathematics)Radiology

Abstract

fetched live from OpenAlex

This work describes the design and use of an inexpensive phantom designed for precision measurements in radiosurgery quality assurance. The main features of this simple phantom include its solid water construction, interchangeable ion chamber holders and film registration system, thus allowing for measurement of small fields with several detectors using the same phantom. The entire phantom was constructed using one 30cm × 30cm × 3cm slab of solid water. The phantom contains a slot that allows for the placement of two small volume ion chambers (liquid and A1SL) via custom inserts near the center of the phantom. In addition, the plug can be filled for film measurements. The phantom can be split down the center to allow for the placement of a film. As opposed to registering film to room based markers, such as lasers, the phantom contains radio-opaque fiducials that puncture the film while also providing a method to register the film images to exported dose planes. In addition to the markers used for film registration, the phantom contains several external beebees that can be used to avoid ambiguity in image registration when using image guidance for setup. This simple phantom contains many features of other much more expensive phantoms designed for this purpose and has been found to be very useful clinically and in departmental research. The key elements of this phantom could be included in several other designs allowing it to be reproduced in other centers.

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)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.003

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 head0.021
GPT teacher head0.341
Teacher spread0.320 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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