Assessing the Performance of the TOFPET2c ASIC at X-ray Energies for Time-of-Flight Scatter Rejection Applications
Bibliographic record
Abstract
The addition of a time-of-flight (ToF) measurements to radiography and computed tomography (CT) opens the door to an anti-scatter grid-free approach to scatter rejection in imaging systems, potentially increasing system sensitivity and image quality. Previously developed hardware limited to a few channels showed that the ToF scatter rejection is possible, but lacked in scale and density. A medium-scale ToF scatter rejection detection module was developed, allowing for the evaluation of off-the-shelf ToF ASICs, as well as the future development of dedicated devices. The TOFPET2c ASIC designed by PETSys showed good potential for the first detector, offering high integration and pixel count. The evaluation of the TOFPET2c ASIC at X-ray energies (20 keV to 140 keV) showed a 414 ps FWHM detector timing resolution. Such a value is slightly over the 300 ps FWHM limit sufficient to reach scatter-rejection similar to anti-scatter grids and requires further investigation. An energy resolution bellow 50% was also reached for all desired energies.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".