SU‐C‐211‐07: Quantitative Reconstruction of Multiplexed Multi‐Pinhole SPECT with Scatter and Attenuation Correction
Bibliographic record
Abstract
Purpose: Small animal microSPECT is an important pre‐clinical imaging modality. However, the quantitative accuracy is limited by photon attenuation in the subject and scatter in the subject and the collimator. In this study we investigate correcting for both scatter and attenuation in the reconstruction of a small animal sized phantom. Methods: A phantom consisting of a cold centre surrounded by a hot shell, surrounded by an outer layer of either water or air, was scanned in a multiplexing multi‐pinhole (MMP) SPECT scanner. Scan parameters were as follows: 9 pinholes/detector, 2.5 mm diameter; 48 projections; helical scan; 3 minutes per projection. Projection data was recorded for two energy windows, one centered at the photopeak (140 keV) and a second window below the photopeak centered at 110 keV. The phantom was also scanned with the built‐in CT scanner (45 keV, cone beam) and reconstructed using filtered backprojection. The SPECT data were reconstructed using an iterative ordered subsets expectation maximization (OSEM) algorithm with no correction, attenuation correction (AC) only, and both scatter (SC) and AC. Attenuation was estimated from the CT and incorporated into the system matrix as part of the reconstruction. Scatter was estimated using the dual energy window method and subtracted from the projections prior to reconstruction. Absolute quantification was derived from a scan of a point source with known activity. Results: With attenuation and scatter correction, the measured activity concentrations in the hot region of the phantom were within 12% of the true value with the external chamber of the phantom both full and empty. Scatter correction in addition to AC improves the accuracy over AC alone in the cold regions. Conclusions: Attenuation correction significantly reduces the subject‐size dependence of the quantitative accuracy in small‐animal MMP SPECT. Scatter correction may provide some additional benefit. Heart and Stroke Foundation of Ontario (NA6374) National Science and Engineering Research Council of Canada (PGS D)
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".