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Record W2130679745 · doi:10.1109/iembs.2007.4352939

Comparison of analytical and algebraic 2D tomographic reconstruction approaches for irregularly sampled microCT data

2007· article· en· W2130679745 on OpenAlex
S. Valton, P. Bérard, Joël Riendeau, Christian Thibaudeau, Roger Lecomte, Dominique Sappey‐Marinier, Françoise Peyrin

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueConference proceedings · 2007
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsDetectorProjection (relational algebra)Iterative reconstructionAlgebraic Reconstruction TechniqueData acquisitionTomographic reconstructionComputer sciencePhysicsComputer visionScannerTomographyOpticsArtificial intelligenceAlgorithm

Abstract

fetched live from OpenAlex

APD-based detectors with individual channel readout were developed for multi-crystal applications and have been implemented for the detection of annihilation radiation in the LabPET micro-scanner. The use of these APD-based detectors in X-ray imaging is currently being assessed with a microCT demonstrator in order to later combine PET and CT in one apparatus. This paper is focused on the tomographic reconstruction of the X-ray transmission data acquired with this demonstrator. Two aspects of the acquisition geometry need to be carefully considered: the radius of the detector arc and the irregular sampling of the detector bins. A specific shift-variant filtered backprojection formula derived to account for the detector curvature is applied to equiangularly resampled projection data while the simultaneous algebraic reconstruction technique is applied to both resampled and original projections. Images of physical phantoms reconstructed from measured projections using the different methods are presented and compared.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.468
Threshold uncertainty score0.401

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 head0.209
GPT teacher head0.390
Teacher spread0.181 · 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