Sinogram-based motion correction of PET images using optical motion tracking system and list-mode data acquisition
Why this work is in the frame
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Bibliographic record
Abstract
Motion of the head during brain positron emission tomography (PET) acquisitions has been identified as a source of artifact in the reconstructed image. A number of techniques have been proposed to correct for this motion artifact, but they are unable to correct for a motion during an acquisition. The aim of this study was to develop a sinogram-based motion correction (SBMC) technique to correct directly the head motion during a PET scan using a motion tracking system and list-mode data acquisition. This method uses a rebinning procedure whereby the lines of response (LOR) are geometrically transformed according to the current values of six-dimensional motion data. A Michelogram was recomposed using the rebinned LOR, and the motion-corrected sinogram was generated. In the motion corrected image, the blurring artifact due to the motion was reduced by the SBMC technique. This technique was applied to actual PET data acquired in the list-mode, and demonstrated the potential for real-time motion correction of head movements during a PET acquisition.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it