Modeling tasks, such as surface deformation and editing, can be analyzed by observing the local behavior of the
surface. We argue that defining a modeling operation by asking for rigidity of the local transformations is useful
in various settings. Such formulation leads to a non-linear, yet conceptually simple energy formulation, which is
to be minimized by the deformed surface under particular modeling constraints. We devise a simple iterative mesh
editing scheme based on this principle, that leads to detail-preserving and intuitive deformations. Our algorithm
is effective and notably easy to implement, making it attractive for practical modeling applications.
形状匹配 医学图像 Skuller A Volumetric Shape Registration Algorithm for Modeling Skull Deformities Medical Image Analysis Yusuf Sahilliog˘lu Ladislav Kavan We present an algorithm for volumetric registration of 3D solid shapes. In comparison to previous work
on image based registration, our technique achieves higher efficiency by leveraging a template tetrahedral
mesh. In contrast to point- and surface-based registration techniques, our method better captures
volumetric nature of the data, such as bone thickness. We apply our algorithm to study pathological skull
deformities caused by a particular condition, i.e., craniosynostosis. The input to our system is a pair of
volumetric 3D shapes: a tetrahedral mesh and a voxelized object represented by a set of voxel cells segmented
from computed tomography (CT) scans. Our general framework first performs a global registration
and then launches a novel elastic registration process that uses as much volumetric information as
possible while deforming the generic template tetrahedral mesh of a healthy human skull towards the
underlying geometry of the voxel cells. Both data are high-resolution and differ by large non-rigid deformations.
Our fully-automatic solution is fast and accurate, as compared with the state of the arts from the
reconstruction and medical image registration fields. We use the resulting registration to match the
ground-truth surfaces extracted from the medical data as well as to quantify the severity of the anatomical
deformity
