3D reconstruction of the spine from biplanar X-rays using parametric models based on transversal and longitudinal inferences
Why this work is in the frame
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Bibliographic record
Abstract
Reconstruction methods from biplanar X-rays provide 3D analysis of spinal deformities for patients in standing position with a low radiation dose. However, such methods require an important reconstruction time and there is a clinical need for fast and accurate techniques. This study proposes and evaluates a novel reconstruction method of the spine from biplanar X-rays. The approach uses parametric models based on longitudinal and transversal inferences. A first reconstruction level, dedicated to routine clinical use, allows to get a fast estimate (reconstruction time: 2 min 30 s) of the 3D reconstruction and accurate clinical measurements. The clinical measurements precision (evaluated on asymptomatic subjects, moderate and severe scolioses) was between 1.2 degrees and 5.6 degrees. For a more accurate 3D reconstruction (complex pathologies or research purposes), a second reconstruction level can be obtained within a reduced reconstruction time (10 min) with a fine adjustment of the 3D models. The mean shape accuracy in comparison with CT-scan was 1.0 mm. The 3D reconstruction method precision was 1.8mm for the vertebrae position and between 2.3 degrees and 3.9 degrees for the orientation. With a reduced reconstruction time, an improved accuracy and precision and a method proposing two reconstruction levels, this approach is efficient for both clinical routine uses and research purposes.
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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 | 0.000 | 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 it