Development of high quantum efficiency flat panel detectors for portal imaging: Intrinsic spatial resolution
Bibliographic record
Abstract
Recently developed flat panel detectors have been proven to have a much better image quality than conventional electronic portal imaging devices (EPIDs). They are, however, not yet the ideal systems for portal imaging application due to the low x-ray absorption, i.e., low quantum efficiency (QE), which is typically on the order of 2-4% as compared to the theoretical limit of 100%. The QE of current flat panel systems can be improved by significantly increasing the thickness of the energy conversion layer (i.e., amorphous selenium or phosphor screen). This, however, will be at the expense of a decrease in spatial resolution mainly due to x-ray scatter in the conversion layer (and also the spread of optical photons in the case of phosphor screen). In this paper, we investigate theoretically the intrinsic spatial resolution of a high QE flat panel detector with a new energy conversion layer that is much denser and thicker than that of current flat panel systems. The modulation transfer function (MTF) of the system is calculated based on a theoretical model using a novel approach, which uses an analytical expression for absorbed dose. It is found that if appropriate materials are used for the conversion layer, then the intrinsic MTF of the high QE flat panel is better than that of current EPIDs, and in addition they have a high QE (e.g., approximately 60%). Some general rules for the design of the conversion layer to achieve both high QE and high resolution as well as high DQE are also discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".