Poster — Thur Eve — 42: Anti‐Scatter Grid Use for Digital Tomosynthesis: An Observer Study
Bibliographic record
Abstract
In digital imaging, an anti‐scatter grid can be placed between the patient and digital detector to improve image contrast, but including the grid also increases the dose to the patient by 2–5 times, depending on the patient thickness. This is of particular concern in the pediatric population because children are more radiosensitive than adults. Since smaller patients produce less scatter, the grid is sometimes removed when imaging small children in order to reduce the dose. However, the default machine protocols at our institution recommend using a grid at most pediatric patient sizes for digital tomosynthesis imaging. We hypothesized that because of the image reconstruction process of tomosynthesis, the final images may be less sensitive to scatter than digital radiography (DR), in which case we should be able to remove the grid for a wide range of pediatric patient sizes without sacrificing a significant level of image quality. To test our hypothesis, we performed an image quality rating study on DR and tomosynthesis images taken with and without the grid for a variety of simulated patient thicknesses. We found that the reconstructed tomosynthesis images did not show a significant reduction in scatter sensitivity compared to DR. Our results suggested that, in general, the grid should be used for all tomosynthesis imaging where the patient thickness is greater than approximately 10 cm. Research supported by GE Healthcare.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".