Real-Time Discrete SPAD Array Readout Architecture for Time of Flight PET
Why this work is in the frame
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Bibliographic record
Abstract
Single photon avalanche diode (SPAD) arrays have proven themselves as serious candidates for time of flight positron emission tomography (PET). Discrete SPAD readout schemes mitigate the low-noise requirements of analog schemes and offer very fine control over threshold levels and timing pickup strategies. On the other hand, a high optical fill factor is paramount to timing performance in such detectors, and consequently space is limited for closely integrated electronics. Nonetheless, a production, daily used PET scanner must minimize bandwidth usage, data volume, data analysis time and power consumption and therefore requires a real-time readout and data processing architecture as close to the detector as possible. We propose a fully digital, embedded real-time readout architecture for SPAD-based detector. The readout circuit is located directly under the SPAD array instead of within or beside it to overcome the fill factor versus circuit capabilities tradeoff. Since the overall real-time engine provides all the required data processing, the system needs only to send the data required by the PET coincidence engine, significantly reducing the bandwidth requirement. A 3D prototype device was implemented in 2 tiers of 130 nm CMOS from Global Foundry / Tezzaron featuring individual readout for 6 scintillator channels. The timing readout is provided by a first photon discriminator and a 31 ps resolution time to digital converter, while energy readout and event packaging is done in real-time using synchronous logic from a CMOS standard cell library, all fully embedded in the ASIC. The dedicated serial output line supports a sustained rate 2.2 Mcps in PET acquisition mode, or 170 kcps in an oscilloscope mode for offline validation and development.
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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 | 0.001 |
| 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 it