Simulation study of cone beam CT for visualizing cell clusters in breast biopsies
Bibliographic record
Abstract
The feasibility of cone beam CT (CBCT) for differentiating normal epithelium from invasive carcinoma is investigated via a simulation study. The phantom consisted of a 5 mm long 5mm diameter cylinder of a 50:50 mixture of fibrous and fatty tissue. Normal epithelium and invasive carcinoma were each modeled as epithelium and connective tissue compartments with respective cross-sectional dimensions of 158 by 161 μm and 131 by 161 μm . For normal epithelium, 125 cells were placed in the compartments with a higher concentration in the basal layer. For the invasive carcinoma, 314 cells were spread out sporadically. Cells were modeled as 5.67 μm diameter spheres. The attenuation coefficients used in the simulation were those of fat for epithelium, 80:20 mixture of fibrous and fat for the connective tissue and water for cells. A point source and 50 μm detector pixels were assumed. Scatter from the phantom is negligible and was neglected. Three hundred projections were acquired at magnification 10 in vacuum using a 26 kV spectrum. The preliminary study suggest a potential application of CBCT for visualizing cell clusters. The contrast was slightly improved by using a 5 to 10 keV uniform spectrum.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".