The x‐ray light valve: A low‐cost, digital radiographic imaging system—Spatial resolution
Bibliographic record
Abstract
An x-ray light valve (XLV) coupled with an optical scanner has the potential to meet the need for a low-cost, high quality digital imaging system for general radiography. The XLV/scanner concept combines three well-established, and hence, low-cost technologies: An amorphous selenium (a-Se) layer as an x-ray-to-charge transducer, a liquid crystal (LC) cell as an analog display, and an optical scanner for image digitization. The XLV consists of an a-Se layer and LC cell in a sandwich structure which produces an optical image in the LC layer upon x-ray exposure. The XLV/scanner system consists of an XLV in combination with an optical scanner for image readout. Here, the effect of each component on the spatial resolution of an XLV/scanner system is investigated. A theoretical model of spatial resolution of an XLV is presented based on calculations of the modulation transfer function (MTF) for a-Se and a LC cell. From these component MTFs, the theoretical MTF of the XLV is derived. The model was validated by experiments on a prototype XLV/scanner system. The MTF of the scanner alone was obtained by scanning an optical test target and the MTF of the XLV/scanner system was measured using x rays. From the measured MTF of the scanner, the theoretical MTF of the XLV/scanner system was established and compared with the experimental results. Good general agreement exists between experimental and theoretical results in the frequency range of interest for general radiography, although the theoretical curves slightly overstate the measured MTFs. The experimental MTF of the XLV was compared with the MTF of two clinical systems and was shown to have the capability to exceed the resolution of flat-panel detectors. From this, the authors can conclude that the XLV has an adequate resolution for general radiography. The XLV/scanner also has the potential to eliminate aliasing while maintaining a MTF that exceeds that of a flat-panel imager.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".