The registration of multimodal images remains an intricate issue, especially when the multimodal image pair shows non overlapping structures, missing data, noise or outliers. In this paper, we present a deformable model-based technique for the rigid registration of 2 0 and 3D multimodal images. The deformable model embeds a priori knowledge of the spatial correspondence and statistical variabil...

Pedicle screw placement for vertebral fixation is a complicated surgery orthopaedic surgeons. The main challenge to estimate the accurate trajectory’s position minimize post-operative complications related pedicle placement. Different types of 3D 2D registration techniques have been employed avoid misplacement during surgery. However, these cannot be applied directly MR X-ray due differences in...

In 1997, Maes et al. [5] was one of the first papers to propose mutual information as a similarity metric for performing multimodal image registration. More than ten years later, mutual information is now found at the core of many state-of-the-art image registration algorithms [2]. The aim of this project is to demonstrate its simplicity, accuracy, and robustness, by implementing the original a...

Automatic registration of multimodal images has proven to be a difficult task. Most existing techniques have difficulty dealing with situations involving highly non-homogeneous image contrast and a small initial overlapping region between the images. This paper presents a robust multi-resolution method for registering multimodal images using local phase-coherence representations. The proposed m...

In this paper we introduce and analyze a method for registering multimodal images with occluding objects in the scene. An analysis of multimodal image registration gives insight into the limitations of assumptions made in current approaches and motivates the methodology of the developed algorithm. Using calibrated stereo imagery, we use maximization of mutual information in sliding corresponden...

Research presented in this paper deals with the systematic examination, development, and evaluation of a novel multimodal registration approach that can perform accurately and robustly for relatively close range surveillance applications. An analysis of multimodal image registration gives insight into the limitations of assumptions made in current approaches and motivates the methodology of the...

In this paper, we develop data driven registration algorithms, relying on pixel similarity metrics, that enable an accurate (subpixel) rigid registration of dissimilar single or multimodal 2D/3D images. Gross dissimilarities are handled by considering similarity measures related to robust M-estimators. In particular, a novel (robust) similarity metric is proposed for comparing multimodal images...

In this paper, we develop data driven registration algorithms, relying on robust pixel similarity metrics, that enable an accurate (subpixel) rigid registration of dissimilar single and multimodal 2D/3D images. A “soft redescending” estimator is associated to a top down stochatic multigrid relaxation algorithm in order to obtain robust, data driven multimodal image registrations. With the stoch...