Non-rigid registration of point clouds is still far from stable,especially for the largely deformed one.Sparse initial correspondences are often adopted to facilitate the process.However,there are few studies on how t...Non-rigid registration of point clouds is still far from stable,especially for the largely deformed one.Sparse initial correspondences are often adopted to facilitate the process.However,there are few studies on how to build them automatically.Therefore,in this paper,we propose a robust method to compute such priors automatically,where a global and local combined strategy is adopted.These priors in different degrees of deformation are obtained by the locally geometrical-consistent point matches from the globally structural-consistent region correspondences.To further utilize the matches,this paper also proposes a novel registration method based on the Coherent Point Drift framework.This method takes both the spatial proximity and local structural consistency of the priors as supervision of the registration process and thus obtains a robust alignment for clouds with significantly different deformations.Qualitative and quantitative experiments demonstrate the advantages of the proposed method.展开更多
As image-guided navigation plays an important role in neurosurgery, the spatial registration mapping the pre-operative images with the intra-operative patient position becomes crucial for a high accurate surgical outp...As image-guided navigation plays an important role in neurosurgery, the spatial registration mapping the pre-operative images with the intra-operative patient position becomes crucial for a high accurate surgical output. Conventional landmark-based registration requires expensive and time-consuming logistic support.Surface-based registration is a plausible alternative due to its simplicity and efficacy. In this paper, we propose a comprehensive framework for surface-based registration in neurosurgical navigation, where Kinect is used to automatically acquire patient's facial surface in a real time manner. Coherent point drift(CPD) algorithm is employed to register the facial surface with pre-operative images(e.g., computed tomography(CT) or magnetic resonance imaging(MRI)) using a coarse-to-fine scheme. The spatial registration results of 6 volunteers demonstrate that the proposed framework has potential for clinical use.展开更多
基金supported by Natural Science Foundation of Anhui Province (2108085MF210,1908085MF187)Key Natural Science Fund of Department of Eduction of Anhui Province (KJ2021A0042)Natural Social Science Foundation of China (19BTY091).
文摘Non-rigid registration of point clouds is still far from stable,especially for the largely deformed one.Sparse initial correspondences are often adopted to facilitate the process.However,there are few studies on how to build them automatically.Therefore,in this paper,we propose a robust method to compute such priors automatically,where a global and local combined strategy is adopted.These priors in different degrees of deformation are obtained by the locally geometrical-consistent point matches from the globally structural-consistent region correspondences.To further utilize the matches,this paper also proposes a novel registration method based on the Coherent Point Drift framework.This method takes both the spatial proximity and local structural consistency of the priors as supervision of the registration process and thus obtains a robust alignment for clouds with significantly different deformations.Qualitative and quantitative experiments demonstrate the advantages of the proposed method.
基金the National Natural Science Foundation of China(Nos.61190120,61190124 and 61271318)the Biomedical Engineering Fund of Shanghai Jiaotong University(No.YG2012ZD06)
文摘As image-guided navigation plays an important role in neurosurgery, the spatial registration mapping the pre-operative images with the intra-operative patient position becomes crucial for a high accurate surgical output. Conventional landmark-based registration requires expensive and time-consuming logistic support.Surface-based registration is a plausible alternative due to its simplicity and efficacy. In this paper, we propose a comprehensive framework for surface-based registration in neurosurgical navigation, where Kinect is used to automatically acquire patient's facial surface in a real time manner. Coherent point drift(CPD) algorithm is employed to register the facial surface with pre-operative images(e.g., computed tomography(CT) or magnetic resonance imaging(MRI)) using a coarse-to-fine scheme. The spatial registration results of 6 volunteers demonstrate that the proposed framework has potential for clinical use.
