X-ray light valve (XLV): a novel detectors' technology for digital mammography
Bibliographic record
Abstract
A novel method, based on X-ray Light Valve (XLV) technology, is proposed for making good image quality yet inexpensive flat panel detectors for digital mammography. The digital mammography markets, particularly in the developing countries, demand quality machines at substantially lower prices than the ones available today. Continuous pressure is applied on x-ray detectors' manufacturers to reduce the flat panel detectors’ prices. XLV presents a unique opportunity to achieve the needed price - performance characteristics for direct conversion, x-ray detectors. The XLV based detectors combine the proven, superior, spatial resolution of a-Se with the simplicity and low cost of liquid crystals and optical scanning. The x-ray quanta absorbed by a 200 μm a-Se produce electron - hole pairs that move under an electric field to the top and bottom of a-Se layer. This 2D charge distribution creates at the interface with the liquid crystals a continuous (analog) charge image corresponding to the impinging radiation's information. Under the influence of local electrical charges next to them, the liquid crystals twist proportionally to the charges and vary their light reflectivity. A scanning light source illuminates the liquid crystals while an associated, pixilated photo-detector, having a 42 μm pixel size, captures the light reflected by the liquid crystals and converts it in16 bit words that are transmitted to the machine for image processing and display. The paper will describe a novel XLV, 25 cm x 30 cm, flat panel detector structure and its underlying physics as well as its preliminary performance measured on several engineering prototypes. In particular, the paper will present the results of measuring XLV detectors' DQE, MTF, dynamic range, low contrast resolution and dynamic behavior. Finally, the paper will introduce the new, low cost, XLV detector based, digital mammography machine under development at XLV Diagnostics Inc.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".