Design, implementation and bench evaluation of a system for automatic synchronization of chest X-ray radiography with peak lung inflation
Bibliographic record
Abstract
The clinical diagnostic data in a chest radiograph is enhanced if chest motion is minimal and X-ray beam exposure occurs at or near peak lung inflation (PLI). Currently, for patients who cannot voluntarily hold a maximal inspiration, beam exposure is manually "synchronized" with PLI and is a hit or miss proposition. We implemented a system for automatically synchronizing beam exposure with PLI during chest radiography. Pressure and bi-directional flow at the airway of patients undergoing positive pressure ventilation are monitored by a personal computer. An algorithm coded in C looks for a zero flow crossing and a peak lung pressure to determine PLI. Custom-built interface electronics allow (a) the system to detect, in real time, which buttons on the X-ray machine handswitch are being pressed by the operator and (b) X-ray beam exposure to be triggered via the software. During bench validation using a mechanical test lung, the system worked consistently, without false triggering. Tests with human patients are currently under way, with IRE approval and informed consent. Preliminary human data indicate that higher quality and more consistent chest radiographs are possible with automatic synchronization of X-ray beam exposure with PLI.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".