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Record W2038740988 · doi:10.1118/1.2907563

Geometric calibration of a mobile C‐arm for intraoperative cone‐beam CT

2008· article· en· W2038740988 on OpenAlexafffund
Michael J. Daly, J. H. Siewerdsen, Y. B. Cho, David A. Jaffray, Jonathan C. Irish

Bibliographic record

VenueMedical Physics · 2008
Typearticle
Languageen
FieldEngineering
TopicAdvanced X-ray and CT Imaging
Canadian institutionsUniversity Health NetworkPrincess Margaret Cancer CentreUniversity of TorontoOntario Institute for Cancer Research
FundersNational Institutes of HealthNational Cancer InstitutePrincess Margaret Hospital FoundationUniversity Health Network
KeywordsDetectorImaging phantomCone beam computed tomographyCalibrationFlat panel detectorOpticsRotation (mathematics)PhysicsReproducibilityImage qualityFull width at half maximumBeam (structure)Nuclear medicineGeometryMathematicsComputer visionComputer scienceMedicineComputed tomography

Abstract

fetched live from OpenAlex

A geometric calibration method that determines a complete description of source-detector geometry was adapted to a mobile C-arm for cone-beam computed tomography (CBCT). The non-iterative calibration algorithm calculates a unique solution for the positions of the source (X(s), Y(s), Z(s)), detector (X(d), Y(d), Z(d)), piercing point (U(o), V(o)), and detector rotation angles (phi, theta, eta) based on projections of a phantom consisting of two plane-parallel circles of ball bearings encased in a cylindrical acrylic tube. The prototype C-arm system was based on a Siemens PowerMobil modified to provide flat-panel CBCT for image-guided interventions. The magnitude of geometric nonidealities in the source-detector orbit was measured, and the short-term (approximately 4 h) and long-term (approximately 6 months) reproducibility of the calibration was evaluated. The C-arm exhibits large geometric nonidealities due to mechanical flex, with maximum departures from the average semicircular orbit of deltaU(o) = 15.8 mm and deltaV(o) = 9.8 mm (for the piercing point), deltaX and deltaY = 6-8 mm and deltaZ = 1 mm (for the source and detector), and deltaphi approximately 2.9 degrees, deltatheta approximately 1.9 degrees, and delta eta approximately 0.8 degrees (for the detector tilt/rotation). Despite such significant departures from a semicircular orbit, these system parameters were found to be reproducible, and therefore correctable by geometric calibration. Short-term reproducibility was < 0.16 mm (subpixel) for the piercing point coordinates, < 0.25 mm for the source-detector X and Y, < 0.035 mm for the source-detector Z, and < 0.02 degrees for the detector angles. Long-term reproducibility was similarly high, demonstrated by image quality and spatial resolution measurements over a period of 6 months. For example, the full-width at half-maximum (FWHM) in axial images of a thin steel wire increased slightly as a function of the time (delta) between calibration and image acquisition: FWHM=0.62, 0.63, 0.66, 0.71, and 0.72 mm at delta = 0 s, 1 h, 1 day, 1 month, and 6 months, respectively. For ongoing clinical trials in CBCT-guided surgery at our institution, geometric calibration is conducted monthly to provide sufficient three-dimensional (3D) image quality while managing time and workflow considerations of the calibration and quality assurance process. The sensitivity of 3D image quality to each of the system parameters was investigated, as was the tolerance to systematic and random errors in the geometric parameters, showing the most sensitive parameters to be the piercing point coordinates (U(o), V(o)) and in-plane positions of the source (X(s), Y(s)) and detector (X(d), Y(d)). Errors in the out-of-plane position of the source (Z(s)) and detector (Z(d)) and the detector angles (phi, theta, eta) were shown to have subtler effects on 3D image quality.

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)0.006
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.012
GPT teacher head0.244
Teacher spread0.232 · 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

Citations83
Published2008
Admission routes2
Has abstractyes

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