AI RESEARCH
Multi-modal 3D Pose and Shape Estimation with Computed Tomography
arXiv CS.CV
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ArXi:2503.19405v2 Announce Type: replace In perioperative care, precise in-bed 3D patient pose and shape estimation (PSE) can be vital in optimizing patient positioning in preoperative planning, enabling accurate overlay of medical images for augmented reality-based surgical navigation, and mitigating risks of prolonged immobility during recovery. Conventional PSE methods relying on modalities such as RGB-D, infrared, or pressure maps often struggle with occlusions caused by bedding and complex patient positioning, leading to inaccurate estimation that can affect clinical outcomes.