  Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET)
automatic 3-D registration is implemented and validated for small animal image
volumes so that the high-resolution anatomical MRI information can be fused
with the low spatial resolution of functional PET information for the
localization of lesion that is currently in high demand in the study of tumor
of cancer (oncology) and its corresponding preparation of pharmaceutical drugs.
Though many registration algorithms are developed and applied on human brain
volumes, these methods may not be as efficient on small animal datasets due to
lack of intensity information and often the high anisotropy in voxel
dimensions. Therefore, a fully automatic registration algorithm which can
register not only assumably rigid small animal volumes such as brain but also
deformable organs such as kidney, cardiac and chest is developed using a
combination of global affine and local B-spline transformation models in which
mutual information is used as a similarity criterion. The global affine
registration uses a multi-resolution pyramid on image volumes of 3 levels
whereas in local B-spline registration, a multi-resolution scheme is applied on
the B-spline grid of 2 levels on the finest resolution of the image volumes in
which only the transform itself is affected rather than the image volumes.
Since mutual information lacks sufficient spatial information, PCA is used to
inject it by estimating initial translation and rotation parameters. It is
computationally efficient since it is implemented using C++ and ITK library,
and is qualitatively and quantitatively shown that this PCA-initialized global
registration followed by local registration is in close agreement with expert
manual registration and outperforms the one without PCA initialization tested
on small animal brain and kidney.
