Motion-compensated targeting in pulmonary interventions using cone-beam CT and locally rigid / globally deformable 3D-2D registration

计算机视觉 图像配准 方向(向量空间) 透视 人工智能 计算机科学 锥束ct 成像体模 初始化 计算机断层摄影术 数学 医学 图像(数学) 放射科 几何学 程序设计语言
作者
Rohan C. Vijayan,Niral Sheth,Lina Mekki,Alexander Lu,Ali Uneri,Alejandro Sisniega,Jessica Maggaragia,Gerhard Kleinszig,Sebastian Vogt,Jeffrey Thiboutot,Hans C. Lee,Lonny Yarmus,Jeffrey H. Siewerdsen
标识
DOI:10.1117/12.2612986
摘要

Purpose. Mobile C-arms capable of 2D fluoroscopy and 3D cone-beam CT (CBCT) are finding application in guidance of transbronchial lung biopsy, but unresolved deformable motion presents challenges to accurate target localization and guidance. We report the initial implementation of a method to resolve deformations via locally rigid / globally deformable 3D-2D registration for motion-compensated overlay of planning data in fluoroscopically-guided pulmonary interventions. Methods. The algorithm proceeds in 3 steps: (1) initialization by 3D-2D rigid registration of CBCT to fluoroscopy (driven by bone gradients); (2) local rigid 3D-2D registration of lung-thresholded CBCT to fluoroscopy within a region of interest (ROI) about each target location; and (3) aggregation of local rigid registrations to estimate global deformation. Several objective functions and optimizers were evaluated for soft-tissue target registration. Phantom studies were performed to determine operating parameters and assess performance with simulated lung deformation. Results. Soft-tissue thresholding and contrast enhancement improved target registration error (TRE) from 10.3 mm for conventional 3D-2D registration (driven primarily by rib gradients) to 3.8 mm using locally rigid 3D-2D registration in regions of interest about each target. The soft-tissue gradient orientation (GO) objective function was found to be superior to alternative similarity measures by de-emphasizing gradient magnitude (in favor of gradient orientation), permitting the algorithm to be better driven by soft-tissue edges. Conclusions. Registration driven by soft-tissue targets is achievable via a novel processing framework to de-emphasize non-target gradients. The proposed method could improve the accuracy of guidance in pulmonary interventions by updating target overlay in fluoroscopy.
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