Performance characterization of a dual-threshold time-over-threshold APD-based detector front-end module for PET imaging
Bibliographic record
Abstract
The LabPET II front-end module is an avalanche photodiode (APD) based pixelated detector designed to achieve submillimetric spatial resolution in pre-clinical Positron Emission Tomography (PET). This technology is also based on Time-over-Threshold (ToT) signal processing and designed to be used as a generic platform for ultra-high resolution PET imaging of small and medium-size animals. The basic building block uses a 4×8 array of 1.12×1.12×12 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> Lu <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1.9</inf> Y <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0.1</inf> SiO <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">5</inf> :Ce (LYSO) scintillator pixels with one-to-one coupling to a 4×8 pixelated APD array mounted on a ceramic carrier. Four of these detectors are mounted on a PCB with two 64-channel ASICs interfacing to two detector modules each. Signals from each APD pixel can be individually processed by dedicated dual-threshold ToT channels providing timing and energy data. Energy calibration was performed using gamma ray sources in the range 300–1275 keV to correct the non-linearity of the ToT signal and obtain energy spectra. Energy and timing performance of the complete front-end module was evaluated. Results confirm the functionality of the dual threshold ToT circuit implemented in the 64-channel ASIC, as well as the physical performance of the most recent LabPET II version of APD-based detectors for applications in high-resolution PET imaging.
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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) | 0.001 | 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".