The Reliability of Foot and Ankle Bone and Joint Kinematics Measured With Biplanar Videoradiography and Manual Scientific Rotoscoping
Bibliographic record
Abstract
The intricate motion of the small bones of the feet are critical for its diverse function. Accurately measuring the 3-dimensional (3D) motion of these bones has attracted much attention over the years and until recently, was limited to invasive techniques or quantification of functional segments using multi-segment foot models. Biplanar videoradiography and model-based scientific rotoscoping offers an exciting alternative that allows us to focus on the intricate motion of individual bones in the foot. However, scientific rotoscoping, the process of rotating and translating a 3D bone model so that it aligns with the captured x-ray images, is either semi- or completely manual and it is unknown how much human error affects tracking results. Thus, the aim of this study was to quantify the inter- and intra-operator reliability of manually rotoscoping in-vivo bone motion of the tibia, talus and calcaneus during running. Three-dimensional CT bone volumes and high-speed biplanar videoradiography images of the foot were acquired on 6 participants. The six-degree-of-freedom motions of the tibia, talus and calcaneus were determined using a manual markerless registration algorithm. Two operators performed the tracking, and additionally, the first operator re-tracked all bones, to test for intra-operator effects. Mean RMS errors were 1.86 mm and 1.90º for intra-operator comparisons and 2.30 mm and 2.60º for inter-operator comparisons across all bones and planes. The moderate to strong similarity values indicate that tracking bones and joint kinematics between sessions and operators is reliable for running. These errors are likely acceptable for defining gross joint angles. However, this magnitude of error may limit the capacity to perform advanced analyses of joint interactions, particularly those that require precise (sub-millimetre) estimates of bone position and orientation. Optimising the view and image quality of the biplanar videoradiography system as well as the automated tracking algorithms for rotoscoping bones in the foot are required to reduce these errors and the time burden associated with the manual processing.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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".