A method for 3D electron density imaging using single scattered x-rays with application to mammographic screening
Bibliographic record
Abstract
Screening mammography is the current standard in detecting breast cancer. However, its fundamental disadvantage is that it projects a 3D object into a 2D image. Small lesions are difficult to detect when superimposed over layers of normal, heterogeneous tissue. In this work, we examine the potential of single scattered photon electron density imaging in a mammographic environment. Simulating a low-energy (<20 keV) scanning pencil beam, we have developed an algorithm capable of producing 3D electron density images from a single projection. We have tested the algorithm by imaging parts of a simulated mammographic accreditation phantom containing lesions of various sizes. The results indicate that the group of imaged lesions differ significantly from background breast tissue (p<0.005), confirming that electron density imaging may be a useful diagnostic test for the presence of breast cancer.
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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 | 0.000 |
| 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".