Measurement of energy and timing resolution of very highly pixellated LYSO crystal blocks with multiplexed SiPM readout for use in a small animal PET/MR insert
Bibliographic record
Abstract
Arrays of silicon photo-multipliers (SiPMs) are good candidates for the readout of detectors in PET MR inserts due to their high packing density, efficiency, low bias voltage and insensitivity to magnetic fields. In this study we report the readout performance of SensL SiPM arrays in terms of their ability to resolve all elements of pixellated lutetium oxy-orthosilicate (LYSO) crystals, and their energy and timing resolution. A SensL SB4-300-35-CER SiPM array consisting of sixteen 3 × 3 mm elements were used as light sensor. An LYSO crystal block consisting of 10×10 1.2 mm × 1.2 mm × 6.0 mm crystals on the bottom layer and 9×9 1.2 mm × 1.2 mm × 4.0 mm crystals on the top layer (which is offset by ½ the crystal width) was mounted on the SensL array, and covers over 95% of its area. A DPC encoding multiplexor with HDMI cable readout made by the Triumf Instrumentation group with a footprint suitable for allowing 16 modules to form a ring inside a Brooker 7T MR rodent imager was used as a readout. The HDMI cable supplies power, and provides readout of four channels and the device temperature. The average energy resolution for all 100 crystals in the lower layer was 11.3±1.8% and 10.8±1.2% for the 81 crystals in the upper layer. The average timing resolution for all 100 crystals in the lower layer was 2.52±0.23 nsec. and 2.55±0.23 nsec. for the 81 crystals in the upper layer.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".