Theoretical analysis and experimental evaluation of a CsI(Tl) based electronic portal imaging system
Bibliographic record
Abstract
This article discusses the design and analysis of a portal imaging system based on a thick transparent scintillator. A theoretical analysis using Monte Carlo simulation was performed to calculate the x-ray quantum detection efficiency (QDE), signal to noise ratio (SNR) and the zero frequency detective quantum efficiency [DQE(0)] of the system. A prototype electronic portal imaging device (EPID) was built, using a 12.7 mm thick, 20.32 cm diameter, Csl(Tl) scintillator, coupled to a liquid nitrogen cooled CCD TV camera. The system geometry of the prototype EPID was optimized to achieve high spatial resolution. The experimental evaluation of the prototype EPID involved the determination of contrast resolution, depth of focus, light scatter and mirror glare. Images of humanoid and contrast detail phantoms were acquired using the prototype EPID and were compared with those obtained using conventional and high contrast portal film and a commercial EPID. A theoretical analysis was also carried out for a proposed full field of view system using a large area, thinned CCD camera and a 12.7 mm thick CsI(TI) crystal. Results indicate that this proposed design could achieve DQE(0) levels up to 11%, due to its order of magnitude higher QDE compared to phosphor screen-metal plate based EPID designs, as well as significantly higher light collection compared to conventional TV camera based systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".