Abstract: method A first image of a moving object is acquired by of a first imaging method, e.g by PET or SPECT imaging. The first image contains artifacts caused by object motion. From two further images acquired by a second imaging method, e.g. C.T. or M.R., and representing the object in respective states of motion, a motion model is formed. The information contents of either the first image or a combination image, formed from the first image and the two further images, and the motion model is enhanced.

Abstract: The present invention relates to a method of computing the transformation for transforming two images (10, 10?), in particular medial MR- or CT-images of a patient, one into the other. The motion pattern at tissue boundaries shows an abrupt change of local transformation parameters that can not be described by continuous transformation functions. To deal with this problem a clustering of corresponding control points (14) is proposed which all have similar or substantial by the same transformation parameters (t1-t4). Criteria for clustering are derived from the local transformation parameters. The transformation parameters for further control points (5, 6, 7), which belong to more than one cluster (C1, C2) are determined in two steps taking into account that the control point (5, 6, 7) could belong to only one of the clusters rather than by performing a conventional interpolation of the transformation parameters of neighbouring control points.

Abstract: The invention relates to a method in which the information contents of an image of a moving object is enhanced. The invention also relates to a system in which such a method can be carried out and to a computer program enabling a data processing unit to carry out such a method. The method is used notably in the field of medical imaging systems. According to the method first a first image of a moving object is acquired by means of a first imaging method, said image containing artifacts which are caused by the object motion. From two further images, acquired by means of a second imaging respective state of motion of the motion, there is formed a motion model which is implemented in a different manner in image processing or image forming steps, so that the information contents of either the first image or a combination image, formed from the first image and the two further images, is enhanced.

Abstract: The invention relates to a method of computing the transformation which transforms two different images (10, 10?) of an object one into the other while describing the motion or deformation of the object. In accordance with the method first the local transformation parameters are computed for sub-regions (1, 2, 3, 4, 5). By choosing the sub-regions so as to be sufficiently small, a rigid transformation can be used for this purpose. Starting from at least one first predetermined sub-region (1), the local transformation parameters of the neighboring sub-regions (2, 3, 4, 5) are successively computed, the starting values on which each computation is based being the already determined local transformation parameters of neighboring sub-regions. Using the local transformation parameters thus determined for sub-regions, the overall transformation can subsequently be computed.

Abstract: The invention relates to a method of forming different images of an object to be examined, notably medical images of a patient, which method includes the steps of:

Abstract: The invention relates to a method of computing the transformation which transforms two different images (10, 10′) of an object one into the other while describing the motion or deformation of the object. In accordance with the method first the local transformation parameters are computed for sub-regions (1, 2, 3, 4, 5). By choosing the subregions so as to be sufficiently small, a rigid transformation can be used for this purpose. Starting from at least one first predetermined sub-region (1), the local transformation parameters of the neighboring sub-regions (2, 3, 4, 5) are successively computed, the starting values on which each computation is based being the already determined local transformation parameters of neighboring sub-regions. Using the local transformation parameters thus determined for sub-regions, the overall transformation can subsequently be computed.