Image Registration Driven by Combined Probabilistic and Geometric Descriptors

Abstract. Deformable image registration in the presence of considerable contrast differences and large-scale size and shape changes represents a significant challenge for image registration. A representative driving application is the study of early brain development in neuroimaging, which requires co-registration of images of the same subject across time or building 4-D population atlases. Growth during the first few years of development involves significant changes in size and shape of anatomical structures but also rapid changes in tissue properties due to myelination and structuring that are reflected in the multi-modal Magnetic Resonance (MR) contrast measurements. We propose a new registration method that generates a mapping between brain anatomies represented as a multi-compartment model of tissue class posterior images and geometries. We transform intensity patterns into combined probabilistic and geometric descriptors that drive the matching in a diffeomorphic framework,...

• Type: Journal
• Year: 2010
• Where: MICCAI
• Authors: Linh K. Ha, Marcel Prastawa, Guido Gerig, John H. Gilmore, Cláudio T. Silva, Sarang C. Joshi
• Keywords: Anatomical Structures, Class Posteriors, Images, Medical Imaging, MICCAI 2010