Registration of organs with sliding interfaces and changing topologies

被引:10
作者
Berendsen, Floris F. [1 ]
Kotte, Alexis N. T. J. [2 ]
Viergever, Max A. [1 ]
Pluim, Josien P. W. [1 ]
机构
[1] Univ Med Ctr Utrecht, Image Sci Inst, POB 85500, NL-3508 GA Utrecht, Netherlands
[2] Univ Med Ctr Utrecht, Dept Radiotherapy, NL-3508 GA Utrecht, Netherlands
来源
MEDICAL IMAGING 2014: IMAGE PROCESSING | 2014年 / 9034卷
关键词
registration; discontinuous deformation field; sliding organs; thorax; DEFORMABLE IMAGE REGISTRATION; MOTION; FRAMEWORK;
D O I
10.1117/12.2043447
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Smoothness and continuity assumptions on the deformation field in deformable image registration do not hold for applications where the imaged objects have sliding interfaces. Recent extensions to deformable image registration that accommodate for sliding motion of organs are limited to sliding motion along approximately planar surfaces or cannot model sliding that changes the topological configuration in case of multiple organs. We propose a new extension to free-form image registration that is not limited in this way. Our method uses a transformation model that consists of uniform B-spline transformations for each organ region separately, which is based on segmentation of one image. Since this model can create overlapping regions or gaps between regions, we introduce a penalty term that minimizes this undesired effect. The penalty term acts on the surfaces of the organ regions and is optimized simultaneously with the image similarity. To evaluate our method registrations were performed on publicly available inhale-exhale CT scans for which performances of other methods are known. Target registration errors are computed on dense landmark sets that are available with these datasets. On these data our method outperforms the other methods in terms of target registration error and, where applicable, also in terms of overlap and gap volumes. The approximation of the other methods of sliding motion along planar surfaces is reasonably well suited for the motion present in the lung data. The ability of our method to handle sliding along curved boundaries and for changing region topology configurations was demonstrated on synthetic images.
引用
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页数:7
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