SU‐GG‐I‐131: Non‐Primary to Primary Ratio Measurements in a Digital Breast Tomosynthesis System
Bibliographic record
Abstract
Purpose: For a breast tomosynthesis system using a stationary detector, a standard mammographic anti‐scatter grid cannot be used. As a result, scatter and off‐focal radiation are expected to be high and will negatively impact reconstructed image quality. In addition, phosphor‐based systems can suffer from glare which will further degrade the image. The goal of this project is to quantify the “non‐primary” sources of signal as a function of projection angle to provide information for potential image correction in the tomosynthesis reconstruction. Method and Materials: The scatter, off‐focal and glare components will be evaluated in terms of a non‐primary to primary ratio (NPR). Using a series of tantalum apertures of increasing size, we measured the primary and off‐focal components, and scatter/glare in an open beam. The NPR was then evaluated over typical tomosynthesis projection angles (0° to 25°) for a range of thicknesses of plastic phantoms. Results: The off‐focal to primary ratio is measured to be 0.091. The NPR at 0° was calculated as 0.44, 0.82, and 1.2 for 2, 4 and 6 cm phantoms. A small angular dependence is seen in the NPR, increasing at higher angles. The NPR can be reasonably predicted by an empirical model of NPR versus effective thickness with a maximum error in NPR of 0.022 (4.9% error) over a range of 0° to 20°. At 25° the NPR appeared to increase sharply (5%–9.5% greater than the empirical model). Conclusion: The NPR appears to be weakly dependent on projection angle up to about 20°. Further investigation will involve extending the measurements to a range of kV and filter combinations, and to elucidate the mechanism for increased NPR at highly oblique angles (>20°). Conflict of Interest (only if applicable): Our lab has a research agreement with GE Healthcare regarding several topics in breast imaging.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".