No single sensor gives us anatomy, posture, and movement at once. These six approaches trade detail, repeatability, and freedom of movement in different ways.
Sensing approaches
Standing radiographs and biplanar X-ray
Clinically established. High value for deformity, alignment, and weight-bearing assessment.
Weight-bearing radiographs remain central to scoliosis, sagittal balance, and deformity analysis. Computer-vision work here focuses on landmarks, Cobb angle estimation, and 3D reconstruction from limited views.
Typical outputs: vertebral landmarks and corners; Cobb angle and global alignment; patient-specific 3D reconstruction from paired views.
Current limits: single-view projection ambiguity; benchmarking is narrower than clinical usage; commercial 3D workflows are more mature than open ML tooling.
Resources: AASCE challenge · EOS 3D modeling
CT anatomy and vertebra segmentation
Strong public benchmark. The best-covered open setting for vertebra labeling and segmentation.
CT provides rich anatomy, robust vertebral boundaries, and multi-center datasets that support automated labeling, segmentation, and morphometric analysis. It is the most benchmark-ready spine-imaging lane today.
Typical outputs: vertebra localization and identification; instance segmentation; morphology and fracture-oriented measurements.
Current limits: structure is captured better than motion; benchmarks emphasize anatomy, not downstream biomechanics; cross-scanner robustness is improving but still matters.
Resources: VerSe challenge
MRI and soft-tissue segmentation
Growing benchmark ecosystem. Strong for discs, vertebrae, canals, and degeneration-related structures.
MRI supports lumbar structure delineation without ionizing radiation and is central for degenerative disease, spinal canal analysis, and soft-tissue context. Open benchmarking exists, but is still less mature than CT.
Typical outputs: vertebra and disc segmentation; canal and foraminal structure delineation; degeneration and pathology assessment.
Current limits: protocol heterogeneity across scanners and institutions; challenge infrastructure exists, but fewer dominant public baselines; biomechanics interpretation is mostly indirect.
Resources: SPIDER challenge
Surface topography and structured light
Clinically useful, weakly benchmarked. Radiation-free follow-up and posture analysis are strong practical advantages.
Rasterstereography and structured-light systems measure back-surface geometry to infer posture and scoliosis-related asymmetries. They are attractive for repeated monitoring, but public ML datasets and common benchmarks are rare.
Typical outputs: back-surface shape and asymmetry; postural screening and progression tracking; non-radiographic follow-up measurements.
Current limits: surface geometry is only an indirect proxy for vertebral anatomy; public datasets are limited; commercial devices dominate over open research infrastructure.
Resources: DIERS formetric 4D · Surface topography review
RGB and multiview markerless motion
Emerging research lane. This is where unconstrained posture and motion finally meet biomechanics-aware supervision.
Conventional pose datasets barely represent the spine beyond shoulders and pelvis. Newer work starts to recover spine-centric 2D landmarks, multiview 3D positions, and vertebral rotations from natural full-body motion.
Typical outputs: 2D spine-centric landmarks; multiview 3D spinal keypoints; vertebral rotations and motion curves.
Current limits: detailed ground truth is scarce; annotation policies differ sharply between datasets; benchmarking is only now becoming reusable.
RGB-D and intraoperative sensing
Early but strategically important. Dense 3D sensing matters when anatomy must be registered during a procedure.
RGB-D and point-cloud methods are emerging for exposed-spine capture, navigation, and registration. The research emphasis is less on general posture and more on anatomically faithful geometry under procedure-time constraints.
Typical outputs: depth completion and point clouds; surface-to-anatomy registration; guidance-ready geometry for navigation.
Current limits: datasets are smaller and more specialized; few field-standard benchmarks exist yet; generalization outside operating-room conditions is unresolved.
Resources: SpineDepth
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