Exploring light confinement in laser-processed LYSO:Ce for photon counting CT application
Bibliographic record
Abstract
With the goal of developing a low-cost scintillator-based photon counting detector (PCD) with high dose efficiency suitable for CT, the light transport characteristics in LYSO:Ce detectors containing laser induced optical barriers (LIOB) are simulated. Light confinement and light collection efficiencies (LCE) are studied for a variety of optical barrier patterns and properties (refractive index (RI) and barrier/crystal interface roughness). Up to 80% confinement is achievable with a simple pixel pattern with one barrier wall separating each pixel coupled one-to-one to a photodetector (PD) pixel. Confinement is heavily dependent on barrier properties, and rough interfaces and higher RI results in increased cross-talk. Three approaches to enhance performance beyond the basic pattern are explored: (1) Multiple barrier walls separating each crystal pixel. (2) Introduction of long and short range confinement by having multiple crystal pixels per PD pixel. (3) Combination of LIOB and laser ablation (LA). (1) Is effective for rough interfaces where confinement can be increased by up to 24% for double compared to single walls. (2) Results in high confinement in the pixel centered on the PD pixel, but lower confinement closer to the PD edge. This feature may be explored to achieve spatial resolution beyond the PD pixel size using light sharing based positioning algorithms. (3) Can increase confinement for smooth interfaces using a smooth ablation in the bottom part of the crystal. A general trend across all configurations is a trade-off between light confinement and LCE. The LCE attainable is found comparable to that for mechanically pixelated arrays. While the confinement achievable with LIOB is always lower compared to a mechanically pixelated array, the former may offer a high level of flexibility in terms of detector design. This, in combination with the possibility to fabricate sub-mm pixels in a cost-effective manner, makes LIOB a promising technology for scintillator-based PCDs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".