X‐ray imaging using avalanche multiplication in amorphous selenium: Investigation of intrinsic avalanche noise
Bibliographic record
Abstract
The flat-panel detector (FPD) is the state-of-the-art detector for digital radiography. The FPD can acquire images in real-time, has superior spatial resolution, and is free of the problems of x-ray image intensifiers-veiling glare, pin-cushion and magnetic distortion. However, FPDs suffer from poor signal to noise ratio performance at typical fluoroscopic exposure rates where the quantum noise is reduced to the point that it becomes comparable to the fixed electronic noise. It has been shown previously that avalanche multiplication gain in amorphous selenium (a-Se) can provide the necessary amplification to overcome the electronic noise of the FPD. Avalanche multiplication, however, comes with its own intrinsic contribution to the noise in the form of gain fluctuation noise. In this article a cascaded systems analysis is used to present a modified metric related to the detective quantum efficiency. The modified metric is used to study a diagnostic x-ray imaging system in the presence of intrinsic avalanche multiplication noise independently from other noise sources, such as electronic noise. An indirect conversion imaging system is considered to make the study independent of other avalanche multiplication related noise sources, such as the fluctuations arising from the depth of x-ray absorption. In this case all the avalanche events are initiated at the surface of the avalanche layer, and there are no fluctuations in the depth of absorption. Experiments on an indirect conversion x-ray imaging system using avalanche multiplication in a layer of a-Se are also presented. The cascaded systems analysis shows that intrinsic noise of avalanche multiplication will not have any deleterious influence on detector performance at zero spatial frequency in x-ray imaging provided the product of conversion gain, coupling efficiency, and optical quantum efficiency are much greater than a factor of 2. The experimental results show that avalanche multiplication in a-Se behaves as an intrinsic noise free avalanche multiplication, in accordance with our theory. Provided good coupling efficiency and high optical quantum efficiency are maintained, avalanche multiplication in a-Se has the potential to increase the gain and make negligible contribution to the noise, thereby improving the performance of indirect FPDs in fluoroscopy.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 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".