Abstract. Mutual information (MI) was introduced for use in multimodal image registration over a decade ago [1,2,3,4]. The MI between two images is based on their marginal and join...
Research presented in this paper deals with the systematic examination, development, and evaluation of a novel multimodal registration approach that can perform accurately and rob...
In the past decade, information theory has been studied extensively in computational imaging. In particular, image matching by maximizing mutual information has been shown to yiel...
Igor Yanovsky, Paul M. Thompson, Stanley Osher, Al...
Over the last five years, new "voxel-based" approaches have allowed important progress in multimodal image registration, notably due to the increasing use of information-...
Abstract. We address the problem of entropy estimation for highdimensional finite-accuracy data. Our main application is evaluating high-order mutual information image similarity c...
Abstract. In this paper we propose a two-step mutual informationbased algorithm for medical image segmentation. In the first step, the image is structured into homogeneous regions,...
Jaume Rigau, Miquel Feixas, Mateu Sbert, Anton Bar...
Abstract. This paper introduces a new similarity measure for multimodal image registration task. The measure is based on the generalized survival exponential entropy (GSEE) and mut...
We propose a new optimizer in the context of multimodal image registration. The optimized criterion is the mutual information between the images to align. This criterion requires ...
Current multimodal registration methods almost always rely on local gradient-descent type optimization strategies. Such registration methods often converge to an incorrect local o...