Sci—Fri AM: Imaging — 03: Temperature dependence of a SiPM detector for an MR compatible PET system
Bibliographic record
Abstract
Silicon photomultiplier (SiPM) detectors are rapidly becoming the detector of choice for research and development of new detectors for positron emission tomography (PET) due to their combination of high gain, fast timing, compact form factor and ability to function in a magnetic field. We are investigating using SiPM based detectors in a compact PET system designed to be inserted into a 7T animal MRI system and enable simultaneous PET/MRI imaging. In order to understand the level of thermal stability required for this PET system, we examined the stability of a prototype SiPM detector vs. temperature. A detector was constructed using a SensL SPMArray4 SiPM array coupled to a LYSO scintillator crystal array. The temperature of the detector was varied between 23 and 60°C in 5°C steps. At each temperature setting data were collected to characterize the detector flood histogram, photopeak amplitude and energy resolution at 511 keV, timing resolution and signal arrival time. While the flood image showed no noticeable changes with temperature, the 511 keV photopeak amplitude showed a linear decrease of 1.5%/°C and the energy resolution degraded by 0.08%/°C. The timing resolution degraded by 1.5 ns, from 3.5 ns to 5 ns when the temperature changed from 23 to 60°C. Over this temperature range there was a shift in the signal arrival time of approximately 3 ns. These results demonstrate that the detector can be operated over a wide range of temperature, giving a large degree of flexibility in choosing an operating temperature set-point for our PET system.
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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".