Comparison of measurement and simulation using GATE with optical photon tracking for a DOI PET detector
Bibliographic record
Abstract
1540 Objectives We are using GATE simulations to model a dual-ended readout LSO based PET detector with DOI capability. In this work we attempt to validate simulations of DOI resolution against previously published experimental results. Methods Simulations including optical photon transport were performed using GATE ver. 4.0.0. Dual-ended readout detectors were simulated with LSO crystals of widths 1.0, 1.3, 1.5 and 2.0 mm and length 20 mm. Side surfaces were set as rough-teflon-wrapped and end surfaces were polished. Each end was coupled to a 9perfect APD9 surface. Crystals were irradiated with a pencil beam source of 511 keV photons oriented perpendicular to the long axis in steps of 2.5 mm. DOI position was calculated as the ratio APD1/(APD1+APD2). DOI resolution was determined as a ratio of the FWHM of the distribution of the ratio signal and its slope versus irradiation depth. Simulated data were compared against published experimental results (Shao et al., IEEE Trans Nuc Sci, 49(3) 2002; Yang et al., Phys Med Biol, 51 2006). Results Table 1 shows the average DOI resolution for the simulated and experimental results. There is agreement in the trend of better resolution with thinner crystal, but systematic differences for events with energy > 350 keV (simulation better than experiment) and for energy Conclusions While GATE results give the general trend in DOI resolution, there are systematic differences that need to be further explored. We are examining the source of these variations through refinements of the simulated optical surfaces. Research Support Supported by funding from NSERC Discovery Grant 360020-2008 and Manitoba Health Research Council Studentship Award.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".