Evaluation of the imaging properties of an amorphous selenium‐based flat panel detector for digital fluoroscopy
Bibliographic record
Abstract
The imaging performance of an amorphous selenium (a-Se) flat-panel detector for digital fluoroscopy was experimentally evaluated using the spatial frequency dependent modulation transfer function (MTF), noise power spectrum (NPS), and detective quantum efficiency (DQE). These parameters were investigated at beam qualities and exposures within the range typical of gastrointestinal fluoroscopic imaging (approximately 0.1 - 10 microR, 75 kV). The investigation does not take into consideration the detector cover, which in clinical use will lower the DQE measured here by its percent attenuation. The MTF was found to be less than the expected aperture response and the NPS was not white which together indicate presampling blurring. The cause of this blurring was attributed to charge trapping at the interface between two different layers of the a-Se. The effect on the DQE was also consistent with presampling blur, which reduces the aliasing in the NPS and thereby reduces the spatial frequency dependence of the DQE. (The DQE was independent of spatial frequency from 0.12 to 0.73 mm(-1) due to antialiasing of the NPS.) Moreover, the first zero of the measured MTF and the aperture response appeared at the same spatial frequency (6.66 mm(-1) for a pixel of 150 microm). Hence, the geometric fill factor (77%) was increased to an effective fill factor of 99 +/- 1%. A large scale ( approximately 32 pixels) correlation in the noise due to the configuration of the readout electronics caused increased noise power in the gate line NPS at low spatial frequency (< 0.1 mm(-1)). The DQE (f = 0) was exposure independent over a large range of exposures but became exposure dependent at low exposures due to the electronic noise.
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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".