MétaCan
Menu
Back to cohort
Record W2066383295 · doi:10.1118/1.4754647

Evaluation of metal artifacts in MVCT systems using a model based correction method

2012· article· en· W2066383295 on OpenAlexafffund
Moti Paudel, M. Mackenzie, B. G. Fallone, S Rathee

Bibliographic record

VenueMedical Physics · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvanced X-ray and CT Imaging
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health ResearchWestern Canada Research GridCompute Canada
KeywordsImaging phantomTomotherapyMaterials scienceBremsstrahlungIterative reconstructionOpticsRodAttenuationPencil (optics)Nuclear medicinePhysicsPhotonComputer scienceArtificial intelligenceRadiation therapyMedicineRadiology

Abstract

fetched live from OpenAlex

PURPOSE: To evaluate the performance of a model based image reconstruction method in reducing metal artifacts in the megavoltage computed tomography (MVCT) images of a phantom representing bilateral hip prostheses and to compare with the filtered-backprojection (FBP) technique. METHODS: An iterative maximum likelihood polychromatic algorithm for CT (IMPACT) is used with an additional model for the pair∕triplet production process and the energy dependent response of the detectors. The beam spectra for an in-house bench-top and TomoTherapy™ MVCTs are modeled for use in IMPACT. The empirical energy dependent response of detectors is calculated using a constrained optimization technique that predicts the measured attenuation of the beam by various thicknesses (0-24 cm) of solid water slabs. A cylindrical (19.1 cm diameter) plexiglass phantom containing various cylindrical inserts of relative electron densities 0.295-1.695 positioned between two steel rods (2.7 cm diameter) is scanned in the bench-top MVCT that utilizes the bremsstrahlung radiation from a 6 MeV electron beam passed through 4 cm solid water on the Varian Clinac 2300C and in the imaging beam of the TomoTherapy™ MVCT. The FBP technique in bench-top MVCT reconstructs images from raw signal normalized to air scan and corrected for beam hardening using a uniform plexiglass cylinder (20 cm diameter). The IMPACT starts with a FBP reconstructed seed image and reconstructs the final image in 150 iterations. RESULTS: In both MVCTs, FBP produces visible dark shading in the image connecting the steel rods. In the IMPACT reconstructed images this shading is nearly removed and the uniform background is restored. The average attenuation coefficients of the inserts and the background are very close to the corresponding values in the absence of the steel inserts. In the FBP images of the bench-top MVCT, the shading causes 4%-9.5% underestimation of electron density at the central inserts with an average of (6.3 ± 1.8)% for the range of electron densities studied. In the uniform plexiglass background, the shadow creates 0.8%-4.7% underestimation of electron density with an average of (2.9 ± 1.2)%. In the corresponding IMPACT images, the underestimation in the shaded plexiglass background is 0.3%-1.8% with an average of (0.9 ± 0.5)% and 1.4%-6.8% with an average of (2.8 ± 2.7)% in the central insert region. In the FBP images of the TomoTherapy™ MVCT, this shading creates 2.6%-6.7% underestimation of electron density with an average of (3.7 ± 1.4)% at the central inserts and 5.9%-7.2% underestimation in the background with an average of (6.4 ± 0.5)%. In the IMPACT images, the uniform background between the steel rods is restored with 0.3%-1.0% underestimation of electron density with an average of (0.7 ± 0.3)%. The corresponding underestimation at the central inserts of the IMPACT images is -0.4%-0.1% with an average of (-0.1 ± 0.2)%. CONCLUSIONS: The shading metal artifact has been nearly removed in MVCT images using the IMPACT algorithm with the accurate geometry of the system, proper modeling of energy dependent response of detectors, and all relevant photon interaction processes. This results less than 1% difference in electron density in the background plexiglass and less than 3% averaged over the range of electron densities investigated.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.850
Threshold uncertainty score0.324

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.066
GPT teacher head0.346
Teacher spread0.280 · 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 designSimulation or modeling
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

Citations12
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueMedical PhysicsSame topicAdvanced X-ray and CT ImagingFrench-language works237,207