LabPET II, a novel 64-channel APD-based PET detector module with individual pixel readout achieving submillimetric spatial resolution
Bibliographic record
Abstract
A new avalanche photodiode (APD) detector module, the LabPET II, was developed to achieve submillimetre spatial resolution for small animal molecular imaging. The module consists of two monolithic APD arrays of 4 × 8 pixels, each with an active area of 1.1 × 1.1 mm2at a 1.2 mm pitch. The two APD arrays are mounted in a custom ceramic holder and coupled to an 8 × 8 LYSO scintillator array designed to accommodate one-to-one coupling between individual APDs and crystal pixels. An analog test board adapted from the LabPET™ processing electronics and consisting of four 16-channel preamplifier ASICs, was designed for testing the LabPET II detector module. The devices have a broad operating range (over 200 V) with breakdown voltage of ∼350 V, at which a typical gain well above 200 is reached. Individual APD pixels have a capacitance of 3.7 ± 0.4 pF (including stray capacitance), a typical dark current of 30 ± 11 nA, a dark noise of 0.13 ± 0.03 pA/Hz½and an equivalent noise charge (ENC) of 12 e−rms at a gain of 100. At a standard APD operating bias, a mean energy resolution of 27.5 ± 2.1% was typically obtained with a relative standard deviation of 13.8% in signal amplitude for the 64 individual pixels when irradiated with 511 keV photons. A global timing resolution of 5.0 ± 0.2 ns FWHM was measured with two modules in coincidence. Finally, an intrinsic spatial resolution of 0.82 ± 0.02 mm FWHM (1.54 ± 0.05 mm FWTM) was obtained by sweeping a22Na point source between two rows of the detector array. By deconvolving the source size and non-collinearity, an expected 0.73 mm intrinsic geometric crystal resolution is obtained. The LabPET II detector module is demonstrating promising characteristics for dedicated small animal PET imaging at submillimetre resolution and, with some further optimization, would be suitable as the building block for a dual-modality combined PET/CT system.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".