Investigation of depth-of-interaction by pulse shape discrimination in multicrystal detectors read out by avalanche photodiodes
Bibliographic record
Abstract
The measurement of depth of interaction (DOI) within detectors is necessary to improve resolution uniformity across the FOV of small diameter PET scanners. DOI encoding by pulse shape discrimination (PSD) has definite advantages as it requires only one readout per pixel and it allows DOI measurement of photoelectric and Compton events. The PSD time characteristics of various scintillators were studied with avalanche photodiodes (APD) and the identification capability was tested in multi-crystal assemblies with up to four scintillators. In the PSD time spectrum of an APD-GSO/LSO/BGO/CsI(Tl) assembly, four distinct peaks at 45, 26, 88 and 150 ns relative to a fast test pulse, having resolution of 10.6, 5.2, 20 and 27 ns, can be easily separated. Whereas the number and position of scintillators affect detector performance, the ability to identify crystals is not compromised. Compton events have a significant effect on PSD accuracy, suggesting that photopeak energy gating should be used for better crystal identification. More sophisticated PSD techniques using parametric time-energy histograms also improve crystal identification in cases where PSD time or energy discrimination alone is inadequate. These results confirm the feasibility of PSD DOI encoding with APDs for PET.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".