Fast 3D reconstruction of the spine from biplanar radiographs using a deformable articulated model
Why this work is in the frame
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Bibliographic record
Abstract
This paper proposes a novel method for fast 3D reconstructions of the scoliotic spine from two planar radiographs. The method uses a statistical model of the shape of the spine for computing the 3D reconstruction that best matches the user input (about 7 control points per radiograph). In addition, the spine was modelled as an articulated structure to take advantage of the dependencies between adjacent vertebrae in terms of location, orientation and shape. The accuracy of the method was assessed for a total of 30 patients with mild to severe scoliosis (Cobb angle [22°, 70°]) by comparison with a previous validated method. Reconstruction time was 90 s for mild patients, and 110 s for severe. Results show an accuracy of ∼0.5mm locating vertebrae, while orientation accuracy was up to 1.5° for all except axial rotation (3.3° on moderate and 4.4° on severe cases). Clinical indices presented no significant differences to the reference method (Wilcoxon test, p ≤ 0.05) on patients with moderate scoliosis. Significant differences were found for two of the five indices (p=0.03) on the severe cases, while errors remain within the inter-observer variability of the reference method. Comparison with state-of-the-art methods shows that the method proposed here generally achieves superior accuracy while requiring less reconstruction time, making it especially appealing for clinical routine use.
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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