Three-Dimensional Reconstruction of the Scoliotic Spine and Pelvis From Uncalibrated Biplanar x-Ray Images
Bibliographic record
Abstract
Current three-dimensional (3D) reconstruction methods based on explicit or implicit calibration procedure require a calibration object to generate calibrated x-rays for the 3D reconstruction of the human spine and the pelvis. However, to conduct retrospective studies where no 3D technology is available, 3D reconstruction must be performed from x-ray images where no calibration object was used. The current state of the art offers a variety of methods to obtain a personalized 3D model of a patient's spine, however, none have presented a clinically proven method which allows a 3D reconstruction using uncalibrated x-rays. The main objective of this study was to propose a self-calibration method using only the anatomic content of the x-ray images and evaluate its clinical feasibility on uncalibrated x-ray images for the 3D reconstruction of the scoliotic spine and pelvis. The rationale for proposing a 3D reconstruction method from uncalibrated x-rays is to allow access to 3D evaluation of spinal deformities in any standard clinical setup and to enable the conduct of retrospective studies of any kind. To assess the validity of the 3D reconstructions yielded by the proposed algorithm, a clinical study using 60 pairs of digitized x-rays of children was conducted. The mean age for this group of 60 patients was of 14+/-3 (range 8 to 18) years old. All the children in the study group had scoliosis, with an average Cobb angle on the frontal plane of 25 degrees (range 3 to 70 degrees). For each case, a 3D reconstruction of the spine and pelvis was obtained using both explicit and self-calibration methods, from calibrated and uncalibrated x-rays, respectively. Results show that 3D reconstructions obtained with the proposed method from uncalibrated x-ray images yield- geometrical models that exhibit insignificant differences for 2D and 3D clinical indices commonly used in the evaluation of spinal deformities. This allows a 3D clinical assessment of scoliotic deformities from standard x-rays without the need for calibration, and providing access to this technology in any clinical setup and allowing to perform retrospective studies, which were previously impossible.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".