A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Inverse C-arm Positioning for Interventional Procedures Using Real-Time Body Part Detection
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
Prediction framework for statistical respiratory motion modeling
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part III
Joint tof image denoising and registration with a CT surface in radiation therapy
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
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Over the last years, range imaging (RI) techniques have been proposed for patient positioning and respiration analysis in motion compensation. Yet, current RI based approaches for patient positioning employ rigid-body transformations, thus neglecting free-form deformations induced by respiratory motion. Furthermore, RI based respiration analysis relies on non-rigid registration techniques with run-times of several seconds. In this paper we propose a real-time framework based on RI to perform respiratory motion compensated positioning and non-rigid surface deformation estimation in a joint manner. The core of our method are pre-procedurally obtained 4-D shape priors that drive the intra-procedural alignment of the patient to the reference state, simultaneously yielding a rigid-body table transformation and a free-form deformation accounting for respiratory motion. We show that our method outperforms conventional alignment strategies by a factor of 3.0 and 2.3 in the rotation and translation accuracy, respectively. Using a GPU based implementation, we achieve run-times of 40 ms.