Calculation and Visualization of Range of Motion of Hip Joint from MRI
Bibliographic record
Abstract
Femoro-Acetabular Impingement (FAI) is a hip joint disease which affects and impairs the range of hip motion during performing activities of daily living, jogging, walking, or climbing stairs due to bony abnormalities of the joint. In this research we introduce a motion simulation and visualization system which helps surgeons to analyze range of hip motions as well as to have a better communication with patients. We evaluate the maximum motion that the joint can achieve from its bony structure if the muscle and other connective tissues are perfectly trained. These goals are achieved by presenting three dimensional (3D) visualizations of motions envelopes by examining maximum possible rotation of the digital hip bones through computer-based simulation. Our computer-based simulation system estimates, analyzes and visualizes the maximum hip range of motion (ROM) for the constructed 3D bone models (femur and pelvis) that are extracted from Magnetic Resonance Images (MRI) after segmenting the bones. These tasks are accomplished first by calculating Hip Joint Center (HJC) which is center of rotation of femoral head followed by simulating hip motions with examining impingement between the femur and the acetabulum using a collision detection system. Six primary plane motions (flexion extension, abduction adduction and internal external rotation) as well as various combinations of these motions and six successive movements are simulated and analyzed along with 3D visualization of estimated range of these motions. Our system by 3D visualization of motions envelopes will provide a platform to understand quicker and better the effect of bony morphology of the hip joint on the possible ROM.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".