An investigation of Lu<inf>1.8</inf>Gd<inf>0.2</inf>SiO<inf>5</inf>:Ce (LGSO) phoswich crystal identification by digital methods
Bibliographic record
Abstract
LGSO-90%Lu scintillators are promising new candidates for future positron emission tomography (PET) scanners, offering high light output (90-120% of NaI(Tl) with avalanche photodiode readout) and a range of decay times from τ = 28 ns to τ = 48 ns by varying cerium concentration during the crystal fabrication process. Such diversity of crystal properties makes it possible to create multiple phoswich detector combinations for improving spatial resolution or measuring depth-of-interaction in PET imaging. This investigation was performed to identify the allowable range of decay time differences that can be used in phoswich detector pairs while still achieving acceptable crystal identification accuracy. The various phoswich arrangements were tested using the LabPET digital electronics implemented with different pulse-shape identification algorithms, including least-mean-square (LMS) auto-regressive method and Wiener filter linear optimization method, to obtain the discrimination error rate. Each phoswich pair was tested with three different low-energy thresholds (150, 250 and 350 keV) to help underlining possible limitations. Overall, the Wiener filter yielded better results. As expected, discrimination was more accurate when using the higher energy threshold of 350 keV. Given an arbitrarily chosen maximum identification error rate of 10%, a decay time difference larger than 12 ns was required with the LMS filter and a 250 keV energy threshold. An even larger decay time difference was required if the slowest crystal decay time was greater than 45 ns. With the Wiener filter and a 250 keV threshold, a decay time difference of only 5 ns was found acceptable if the slowest crystal decay time was under 38 ns. In contrast, when the fastest crystal decay time was higher than 38 ns, a decay time difference of 10 ns or more was required. In summary, when using a Wiener filter-based identification algorithm, a relatively wide range of LGSO crystal combinations can be used to achieve accurate crystal identification in phoswich detectors for 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 | 0.001 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".