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Advancing Accuracy in Orthopedic Imaging

AI-Driven Segmentation on Weight Bearing CT Introduction Accurate segmentation is critical for orthopedic workflows, including preoperative planning, patient-specific instrumentation, and 3D modeling. This internal investogation by CurveBeam AI evaluates the accuracy of AI-driven segmentation compared to manual annotation on CBCT…

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SegmentationPreviewwPlay

Sub-Millimeter Accuracy in Weight-Bearing Orthopedic Imaging

Orthopedic decision-making depends on accurate representation of anatomy—particularly when joint alignment and bone relationships change under load. Conventional supine imaging can obscure these functional differences, creating uncertainty in assessment and surgical planning. A recent internal investigation evaluated whether weight-bearing cone…

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WilleyHipStudy

Supine CT May Underestimate Contact Stress in Critical WB Regions of the Acetabulum Compared to Weight Bearing CT

Key Points: Computational models of the hip often omit patient-specific functional orientation when placing imaging-derived bony geometry into anatomic landmark-based coordinate systems for application of joint loading schemes. Significant differences are found when incorporating WBCT-derived data suggesting non-weight bearing (NWB)…

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