SU-E-I-51: Quantitative Assessment of X-Ray Imaging Detector Performance in a Clinical Setting - a Simple Approach Using a Commercial Instrument
Bibliographic record
Abstract
Purpose: To measure and compare the performance of X-ray imaging detectors in a clinical setting using a dedicated instrument for the quantitative determination of detector performance. Methods: The DQEPro (DQE Instruments Inc., London, Ontario Canada) was used to determine the MTF, NPS and DQE using an IEC compliant methodology for three different imaging modalities: conventional radiography (CsI-based detector), general-purpose radioscopy (CsI-based detector), and mammography (a-Se based detector). The radiation qualities (IEC) RQA-5 and RQA-M-2 were used for the CsI-based and a-Se-based detectors, respectively. The DQEPro alleviates some of the difficulties associated with DQE measurements by automatically positioning test devices over the detector, guiding the user through the image acquisition process and providing software for calculations. Results: A comparison of the NPS showed that the image noise of the a-Se detector was less correlated than the CsI detectors. A consistently higher performance was observed for the a-Se detector at all spatial frequencies (MTF: [email protected] cy/mm, DQE: [email protected] cy/mm) and the DQE drops off slower than for the CsI detectors. The CsI detector used for conventional radiography displayed a higher performance at low spatial frequencies compared to the CsI detector used for radioscopy (DQE: 0.65 vs [email protected] cy/mm). However, at spatial frequencies above 1.3 cy/mm, the radioscopy detector displayed better performance than the conventional radiography detector (DQE: 0.35 vs [email protected] cy/mm). Conclusion: The difference in the MTF, NPS and DQE that was observed for the two different CsI detectors and the a-Se detector reflect the imaging tasks that the different detector types are intended for. The DQEPro has made the determination and calculation of quantitative metrics of X-ray imaging detector performance substantially more convenient and accessible to undertake in a clinical setting.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".