Simultaneous Geometric -Iconic Registration

摘要：

In this paper, we introduce a novel approach to bridge the gap between the landmark-based and the iconic-based voxel-wise registration methods. The registration problem is formulated with the use of Markov Random Field theory resulting in a discrete objective function consisting of thee parts. The first part of the energy accounts for the iconic-based volumetric registration problem while the second one for establishing geometrically meaningful correspondences by optimizing over a set of automatically generated mutually salient candidate pairs of points. The last part of the energy penalizes locally the difference between the dense deformation field due to the iconic-based registration and the implied displacements due to the obtained correspondences. Promising results in real MR brain data demonstrate the potentials of our approach.

作者: Aristeidis Sotiras Yangming Ou Ben Glocker Christos Davatzikos Nikos Paragios

作者单位: Laboratoire MAS, Ecole Centrale de Paris, FranceEquipe GALEN, INRIA Saclay - Ile de France, France Section of Biomedical Image Analysis (SBIA), University of Pennsylvania, USA Computer Aided Medical Procedures (CAMP), Technische Universitat Munchen, Germany Laboratoire MAS, Ecole Centrale de Paris, France Equipe GALEN, INRIA Saclay - Ile de France, France

会议类型: 国际会议

会议名称: The 13th International Conference on Medical Image Computing and Computer-Assisted Intervention(第13届医学影像计算与计算机辅助介入国际会议 MICCAI 2010)

会议地点: 北京

会议语种:英文

页码: 676–683

在线出版日期: 2010-09-01（万方平台首次上网日期，不代表论文的发表时间）