3D reconstruction of the pelvis from bi-planar radiography
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
3D personalized models are more and more requested for clinical and biomechanical studies. Techniques based on bi-planar X-rays present the advantage of a low radiation dose for the patient. However, up to now, such techniques have shown limited accuracy in the case of pelvis reconstruction. This study proposes and validates a method providing accurate 3D personalized model of the pelvis from bi-planar X-rays. The algorithm is based on the fast computation of an initial solution followed by local deformations based on 2D anatomical points and contours that are digitized in both radiographs. Results were close to CT-scan reconstructions (mean difference 1.6 mm and differences under 4.3 mm for 95% of the points). Moreover, 3D morphometry of the pelvis could be obtained with an accuracy of 5%. This technique provides 3D patient specific model with a low radiation dose.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 it