Using additive manufacturing in accuracy evaluation of reconstructions from computed tomography
Bibliographic record
Abstract
Bone models derived from patient imaging and fabricated using additive manufacturing technology have many potential uses including surgical planning, training, and research. This study evaluated the accuracy of bone surface reconstruction of two diarthrodial joints, the hip and shoulder, from computed tomography. Image segmentation of the tomographic series was used to develop a three-dimensional virtual model, which was fabricated using fused deposition modelling. Laser scanning was used to compare cadaver bones, printed models, and intermediate segmentations. The overall bone reconstruction process had a reproducibility of 0.3 ± 0.4 mm. Production of the model had an accuracy of 0.1 ± 0.1 mm, while the segmentation had an accuracy of 0.3 ± 0.4 mm, indicating that segmentation accuracy was the key factor in reconstruction. Generally, the shape of the articular surfaces was reproduced accurately, with poorer accuracy near the periphery of the articular surfaces, particularly in regions with periosteum covering and where osteophytes were apparent.
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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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".