Learning Best Features and Deformation Statistics for Hierarchical Registration of MR Brain Images

A fully learning-based framework has been presented for deformable registration of MR brain images. In this framework, the entire brain is first adaptively partitioned into a number of brain regions, and then the best features are learned for each of these brain regions. In order to obtain overall better performance for both of these two steps, they are integrated into a single framework and solved together by iteratively performing region partition and learning the best features for each partitioned region. In particular, the learned best features for each brain region are required to be identical, and maximally salient as well as consistent over all individual brains, thus facilitating the correspondence detection between individual brains during the registration procedure. Moreover, the importance of each brain point in registration is evaluated according to the distinctiveness and consistency of its respective best features, therefore the salient points with distinctive and consist...

• Type: Conference
• Year: 2007
• Where: IPMI
• Authors: Guorong Wu, Feihu Qi, Dinggang Shen
• Keywords: Brain Deformations, Brain Regions, IPMI 2007, Learning-based Registration Framework, Medical Imaging