Ghosting caused by bulk charge trapping in direct conversion flat-panel detectors using amorphous selenium
Bibliographic record
Abstract
Direct flat-panel detectors using amorphous selenium (a-Se) x-ray photoconductors are gaining wide-spread clinical use. The goal of our investigation is to understand the physical mechanisms responsible for ghosting, i.e., x-ray induced change in sensitivity that results in image persistence, so that the knowledge can be used to consistently minimize ghosting artifacts in a-Se flat-panel detectors. In this paper we will discuss the effect on x-ray sensitivity of charge trapping in a-Se, which is the dominant source for ghosting in a-Se flat-panel detectors. Our approach is to correlate ghosting in electroded a-Se detectors with the trapped charge concentration measured by the "time-of-flight" (TOF) method. All measurements were performed as a function of radiation exposure X of up to approximately 20 R at electric field strength's of E(Se)=5 and 10 V/microm. The results showed that the x-ray sensitivity decreased as a function of X and the amount of ghosting decreased with increasing E(Se). The shape of the TOF curves changed as a result of irradiation in a manner indicating trapped electrons in the bulk of a-Se. The density of trapped electrons n(t) increases as a function of X. A method was developed to determine the values of n(t) in the bulk of a-Se from the TOF measurements, and to predict the corresponding change in x-ray sensitivity. Our results showed that a recombination coefficient consistent with that predicted by Langevin produced good agreement between calculated and measured x-ray sensitivity changes. Thus it can be concluded that the trapping of electrons in the bulk of a-Se and their subsequent recombination with x-ray generated free holes is the dominant mechanism for ghosting in a-Se.
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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 | 0.003 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".