Double-Decomposition Motion Tracking of Intraoperative 3D Structures via Cross-Spatio-Temporal Semantics Alignment

3D motion tracking in X-ray image-guided operations using pre- and intra-operative image registration has recently gained attention. However, due to pre- and intra-operative acquisitions exist spatio-temporal misalignment (i.e., limited 3D prior versus continuous 2D images) and distinct respiratory phase difference, recent methods still struggle to accurately estimate 3D dynamic structures from X-ray images. To overcome these issues, we propose a novel double-decomposition tracking (DD-Track) framework that aligns with multi-organ motion characteristics via two alignment pipes: 1) Temporal alignment aims to compensate in-plane respiratory phases difference between the projection of static 3D prior and continuous X-ray images. A dual-excitation mechanism in the image and frequency domains is proposed to extract discriminate motion features while suppressing irrelevant background information. 2) Spatial alignment subsequently integrates the extracted 2D motion features into the cross-modal registration process to accurately warp the 3D prior. Further, we decompose the motion tracking into the common trajectory and organ-specific deformation to align with the multi-organ motion nature, avoiding excessive organ stretching for sliding compensation. Comprehensive quantitative and qualitative experiments on simulated and clinical multi-organ datasets demonstrate that DD-Track outperforms state-of-the-art methods, and we also validate its generalization for tracking intra-organ lesions on simulated data.