Introduction: The purpose of multimodal and co-registration In MR Neuroimaging is to fuse two or more sets images (T1, T2, fMRI, DTI, pMRI, …) for combining the different information into a composite correlated data set in order to visualization, re-alignment and generating transform to functional Matrix. Multimodal registration and motion correction in spinal cord MR Neuroimag...

RATIONALE AND OBJECTIVES The aim of this study was to develop non-rigid image registration between preprocedure contrast-enhanced magnetic resonance (MR) images and intraprocedure unenhanced computed tomographic (CT) images, to enhance tumor visualization and localization during CT imaging-guided liver tumor cryoablation procedures. MATERIALS AND METHODS A non-rigid registration technique was...

This paper presents a validation study for non-rigid registration of 3D contrast enhanced magnetic resonance mammography images. We compare the performance of two non-rigid registration algorithms based on singleand multilevel free-form deformations using B-splines and normalized mutual information. To assess the registration performance, we employ a biomechanical deformation simulator of patie...

In this paper, we describe feature-based nonrigid registration of histological serial section images. Our method represents non-rigid deformation by blending the rigid transformations estimated in the local region around a control point. This approach can efficiently represent nonrigid deformation with a smaller number of control points than conventional methods that interpolate displacement, s...

The exact localization of intrahepatic vessels in relation to a tumour is an important issue in oncological liver surgery. For computer-assisted preoperative planning of surgical procedures high quality vessel models are required. In this work we show how to generate such models on the basis of registered CT or MRI data at different phases of contrast agent propagation. We combine well-establis...

In this paper we present a new approach for the non-rigid registration of contrast-enhanced breast MRI. A hierarchical transformation model of the motion of the breast has been developed: The global motion of the breast is modelled by an a ne transformation while the local breast motion is described by a free-form deformation (FFD) based on B-splines. Normalised mutual information is used as a ...

Non-rigid mutual information (MI) based image registration is prone to converge to local optima due to Parzen or histogram based density estimation used in conjunction with estimation of a high dimensional deformation field. We describe an approach for non-rigid registration that uses the log-likelihood of the target image given the deformed template as a similarity metric, wherein the distribu...