title: [Method of multi-resolution 3D image registration by mutual information].
abstract: Maximization of mutual information is a powerful criterion for 3D medical image registration, allowing robust and fully accurate automated rigid registration of multi-modal images in a various applications. In this paper, a method based on normalized mutual information for 3D image registration was presented on the images of CT, MR and PET. Powell's direction set method and Brent's one-dimensional optimization algorithm were used as optimization strategy. A multi-resolution approach is applied to speedup the matching process. For PET images, pre-procession of segmentation was performed to reduce the background artefacts. According to the evaluation by the Vanderbilt University, Sub-voxel accuracy in multi-modality registration had been achieved with this algorithm.
authors.affiliation: Department of Nuclear Medicine, Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100021.
authors.forename: Haiping
authors.initials: H
authors.lastname: Ren
authors.forename: Wenkai
authors.initials: W
authors.lastname: Wu
authors.forename: Hu
authors.initials: H
authors.lastname: Yang
authors.forename: Shengzu
authors.initials: S
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional