Comparison of CsI:Tl and Gd<sub>2</sub>O<sub>2</sub>S:Tb indirect flat panel detector x‐ray imaging performance in front‐ and back‐irradiation geometries
Bibliographic record
Abstract
Purpose The detective quantum efficiency (DQE) of indirect flat panel detectors (I‐FPDs) is limited at higher x‐ray energies (e.g., 100–140 kVp) by low absorption in their scintillating x‐ray conversion layer. While increasing the thickness of the scintillator can improve its x‐ray absorption efficiency, this approach is potentially limited by reduced spatial resolution and increased noise due to depth dependence in the scintillator’s response to x rays. One strategy proposed to mitigate these deleterious effects is to irradiate the scintillator through the pixel sensor in a “back‐irradiation” geometry. This work directly evaluates the impact of irradiation geometry on the inherent imaging performance of I‐FPDs composed with columnar CsI:Tl and powder Gd 2 O 2 S:Tb (GOS) scintillators. Methods A “bidirectional” FPD was constructed which allows scintillator samples to be interchangeably coupled with the detector’s active matrix to compose an I‐FPD. Radio‐translucent windows in the detector’s housing permit imaging in both “front‐irradiation” (FI) and “back‐irradiation” (BI) geometries. This test device was used to evaluate the impact of irradiation geometry on the x‐ray sensitivity, modulation transfer function (MTF), noise power spectrum (NPS), and DQE of four I‐FPDs composed using columnar CsI:Tl scintillators of varying thickness (600–1000 µm) and optical backing, and a Fast Back GOS screen. All experiments used an RQA9 x‐ray beam. Results Each I‐FPD’s x‐ray sensitivity, MTF, and DQE was greater or equal in BI geometry than in FI. The I‐FPD composed with CsI:Tl (1 mm) and an optically absorptive backing had the largest variation in sensitivity (17%) between FI and BI geometries. The detector composed with GOS had the largest improvement in limiting resolution (31%). Irradiation geometry had little impact on MTF( f ) and DQE( f ) measurements near zero frequency, however, the difference between FI and BI measurements generally increased with spatial frequency. The CsI:Tl scintillator with optically absorptive backing (1 mm) in BI geometry had the highest spatial resolution and DQE over all frequencies. Conclusions Back irradiation may improve the inherent x‐ray imaging performance of I‐FPDs composed with CsI:Tl and GOS scintillators. This approach can be leveraged to improve tradeoffs between detector dose efficiency, spatial resolution and noise for higher energy x‐ray imaging.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".