Evaluation of SiPM photodetectors for use in phoswich detectors
Bibliographic record
Abstract
MR compatible PET is an attractive hybrid modality for preclinical small animal studies. Small ring diameter PET systems, such as those needed to fit inside an MR bore, tend to suffer from radial blurring due to parallax error away from the center of the FOV. To reduce this error a phoswich design can be adopted where layers of different scintillation materials are identified by decay time characteristics. This design requires a photo-detector and electronics capable of discriminating between different scintillator decay times. The benefits of a phoswich design in a PET/MR system can only be realized using MR compatible photo detectors capable of decay time identification. Photomultiplier tubes (PMTs) and avalanche photo diodes (APDs) have traditionally been used in phoswich detectors, however PMTs are unsuitable for use in a magnetic field and APDs pose a challenge due to their low gain and relatively poor timing characteristics. Silicon photomultipliers (SiPMs) are MR compatible but have not been extensively studied for use in phoswich detectors. In this work, we compare the scintillation decay time identification capability of two SiPM models, the SensL MicroFB-SMA-30035 and the Hamamatsu S10985-050C, for two scintillation pairs LGSO/LYSO and LSO:Ce,Ca(0.1%)/LSO:Ce,Ca(0.3%). The two SiPMs were compared to a Hamamatsu H3178-51 PMT. Data was acquired by capturing waveforms using a DRS4 evaluation board. The fall time histograms of the SiPMs from 80-20% of the signal shows that the Hamamatsu MPPC has better decay time separation and thus, better phoswich potential than the SensL SiPM. However, the Hamamatsu PMT shows better decay time separation than both of the SiPMs.
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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) | 0.001 | 0.000 |
| 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) | 0.001 | 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".