Adaptive mesh generation for image registration and segmentation

This paper deals with the problem of generating quality tetrahedral meshes for image registration. From an initial coarse mesh the approach matches the mesh to the image volume by combining red-green subdivision and mesh evolution through mesh-to-image matching regularized with a mesh quality measure. The method was tested on a T1 weighted MR volume of an adult brain and showed a 66% reduction in the number of mesh vertices compared to a red-subdivision strategy. The deformation capability of the mesh was tested by registration to five additional T1-weighted MR volumes.