3D ultrasonic visualization of hip displacement: A phantom study
Bibliographic record
Abstract
Hip displacement is common in children with cerebral palsy (CP). Reimer's migration percentage (MP) measured on radiographs is the gold standard for assessing hip displacement. This phantom study was a proof-of-concept investigation, which aimed to evaluate the accuracy of MP measurements on the 3D reconstructed ultrasound (US) hip images. Two 3D printed pediatric hip phantoms with known MPs were scanned anteriorly along the superior-inferior direction to acquire two series of 2D US transverse images at 0.5 mm intervals using a handheld ultrasound scanner. Following image acquisition, the 2D images were consecutively stacked to create 3D reconstructed images. A morphological operation was applied to the coronal slices of the 3D images to correct for elevation thickness artifacts. Least-squares sphere fitting was employed to estimate the width of the femoral head (FH). A comparison of the measured MPs from the reconstructed US images and digital phantoms was reported. The US MP-values were also compared with those from clinical standard radiography and 2D circle-fitting method. The proposed 3D US method delivered the most accurate MP measurements up to a maximum error of 1.16 % compared to the ground truth phantom measurements. In contrast, the radiography and circle-fitting methods were off by 7.6 % and 16.82 %, respectively. The proof-of-concept study using phantoms has shown that the US-based measurements from 3D images provide much more accurate MP-values than the conventional X-ray method and 2D-based US measurements. Further validation using in-vivo data will show the potential of the radiation-free method in providing better patient care.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".