The x‐ray light valve: A potentially low‐cost, digital radiographic imaging system—a liquid crystal cell design for chest radiography
Bibliographic record
Abstract
Digital x-ray radiographic systems are desirable as they offer high quality images which can be processed, transferred, and stored without secondary steps. However, current clinical systems are extraordinarily expensive in comparison to film-based systems. Thus, there is a need for an economical digital imaging system for general radiology. The x-ray light valve (XLV) is a novel digital x-ray detector concept with the potential for high image quality and low cost. The XLV is comprised of a photoconductive detector layer and liquid crystal (LC) cell physically coupled in a sandwich structure. Upon exposure to x rays, charge is collected at the surface of the photoconductor, causing a change in the reflective properties of the LC cell. The visible image so formed can subsequently be digitized with an optical scanner. By choosing the properties of the LC cell in combination with the appropriate photoconductor thickness and bias potentials, the XLV can be optimized for various diagnostic imaging tasks. Specifically for chest radiography, we identified three potentially practical reflective cell designs by selecting from those commonly used in LC display technology. The relationship between reflectance and x-ray exposure (i.e., the characteristic curve) was determined for all three cells using a theoretical model. The results indicate that the reflective electrically controlled birefringence (r-ECB) cell is the preferred choice for chest radiography, provided that the characteristic curve can be shifted towards lower exposures. The feasibility of the shift of the characteristic curve is shown experimentally. The experimental results thus demonstrate that an XLV based on the r-ECB cell design exhibits a characteristic curve suitable for chest radiography.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 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".