Physical characteristics of a low‐dose gas microstrip detector for orthopedic x‐ray imaging
Bibliographic record
Abstract
A new scanning slit gas detector dedicated to orthopedic x-ray imaging is presented and evaluated in terms of its fundamental imaging characteristics. The system is based on the micromesh gaseous structure detector and achieves primary signal amplification through electronic avalanche in the gas. This feature, together with high quantum detection efficiency and fan-beam geometry, allows for imaging at low radiation levels. The system is composed of 1764 channels spanning a width of 44.8 cm and is capable of imaging an entire patient at speeds of up to 15 cm/s. The resolution was found to be anisotropic and significantly affected by the beam quality in the horizontal direction, but otherwise sufficient for orthopedic studies. As a consequence of line-by-line acquisition, the images contain some ripple components due to mechanical vibrations combined with variations in the x-ray tube output power. The reported detective quantum efficiency (DQE) values are relatively low (0.14 to 0.20 at 0.5 mm(-1)) as a consequence of a suboptimal collimation geometry. The DQE values were found to be unaffected by the exposure down to 7 microGy, suggesting that the system is quantum limited even for low radiation levels. A system composed of two orthogonal detectors is already in use and can produce dual-view full body scans at low doses. This device could contribute to reduce the risk of radiation induced cancer in sensitive clientele undergoing intensive x-ray procedures, like young scoliotic women.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".