Abstract: A method of combining a first image of a first region and a second image of a second region, having an overlapping region therebetween. The method including determining a superposed image as a weighted superposition of the first image and the second image in the overlap region, transforming the first image and the second image on the basis of a comparison of at least one of the first image and the second image with the determined superposed image; determining a further superposed image from the transformed first image and the transformed second image; and generating an overall image from the further superposed image when at least one convergence criterion is satisfied.

Abstract: A method for registering digitized images using Markov Random Fields (MRFs) includes providing a source image f and a target image g, defining a deformation grid of control points, defining a coordinate transformation as T ? ( x ) = x + ? p ? G ? ? ? ( ? x - p ? ) ? d u p , where x is a point on the source image, p is a position vector of control point p, dp is a displacement vector for each control point, up is a label for point p associated with displacement dp, and ?( ) is a weighting function for the displacement vector, defining an MRF energy functional to be minimized by T as E t = 1 ? G ? ? ? p ? G ? V p t ? ( u p ) + 1 ? E ? ? ? p , q ? E ? V pq ? ( u p , u q ) , wherein |G| is a number of control points, |E| is a number of pairs of neighboring control points on a neighborhood system, t is an iteration counter, and associating the MRF with a primary linear program and solving the primary linear program usi

Abstract: A method is disclosed for combining a first image and a second image of an examination object, which images have an overlap region. A corresponding magnetic resonance scanner is also disclosed. In at least one embodiment, a superposed image is determined in the overlap region as a weighted superposition of the first image and the second image with a spatially variable weighting function. The first image and the second image are transformed on the basis of a comparison of the first image and/or the second image with the superposed image.

Abstract: A method for registering digitized images using Markov Random Fields (MRFs) includes providing a source image f and a target image g, defining a deformation grid of T ? ( x ) = x + ? p ? G ? ? ? ( ? x - p ? ) ? d u p , control points, defining a coordinate transformation as where x is a point on the source image, p is a position vector of control point p, dp is a displacement vector for each control point, up is a label for point p associated with displacement dp, and ?( ) is a weighting function for the displacement vector, defining an MRF energy functional to be minimized by T as E t = 1 ? G ? ? ? p ? G ? V p t ? ( u p ) + 1 ? E ? ? ? p , q ? E ? V pq ? ( u p , u q ) , wherein |G| is a number of control points, |E| is a number of pairs of neighboring control points on a neighborhood system, t is an iteration counter, and associating the MRF with a primary linear program and solving the primary linear program usin