ATTENUATION CORRECTION IN CARDIAC PET/CT USING A TIME- AVERAGED CT
Bibliographic record
Abstract
Heart disease is a leading cause of death in Canada, and Positron Emission Tomography (PET) is the gold standard for determining the viability of heart tissue following a heart attack. PET images require correction for attenuation, that is, for signal absorption by patient tissues. Attenuation correction (AC), is done via a transmission scan such as Computed Tomography (CT). However, due to the differences between PET and CT scan durations, respiration-induced motion can cause temporal mismatches leading to errors in the reconstructed PET image. This study compares the magnitude of these errors when single-phase CT, respiratory-averaged CT, and 4D CT are used for AC of cardiac PET in an in vivo canine model. The respiratory-averaged CT correction produced maximum percentage differences that were 7 times less than those produced by the single-phase correction. Using a respiratory-averaged CT may provide an accurate form of AC for cardiac PET imaging.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".