Abstract: A method (30) for image registration of sections, in particular for image registration of histological sections, is described. The method comprises reading in (32) of a data set for at least two sections, wherein each of the data sets comprises m images of each section in m resolution levels (11, 12, 13), wherein each image of the resolution levels 1 to m?1 is divided into at least two cells, wherein each image has a different image resolution, wherein the image with the highest image resolution is associated with the resolution level 1 and the image with the lowest image resolution is associated with the resolution level m; registering (33) of the two mth images of the two sections on the resolution level m and determining of a global transformation for the resolution level m; aligning (34) of the two images of the resolution level m?1 using the global transformation of the resolution level m; and registering (35) of a subgroup of cells from all cells of the two images of the resolution level m?1.

Abstract: A method (30) for image registration of sections, in particular for image registration of histological sections, is described. The method comprises reading in (32) of a data set for at least two sections, wherein each of the data sets comprises m images of each section in m resolution levels (11, 12, 13), wherein each image of the resolution levels 1 to m?1 is divided into at least two cells, wherein each image has a different image resolution, wherein the image with the highest image resolution is associated with the resolution level 1 and the image with the lowest image resolution is associated with the resolution level m; registering (33) of the two mth images of the two sections on the resolution level m and determining of a global transformation for the resolution level m; aligning (34) of the two images of the resolution level m?1 using the global transformation of the resolution level m; and registering (35) of a subgroup of cells from all cells of the two images of the resolution level m?1.

Abstract: A method for performing deformable non-rigid registration of 2D and 3D images of a vascular structure for assistance in surgical intervention includes acquiring 3D image data. An abdominal aorta is segmented from the 3D image data using graph-cut based segmentation to produce a segmentation mask. Centerlines are generated from the segmentation mask using a sequential topological thinning process. 3D graphs are generated from the centerlines. 2D image data is acquired. The 2D image data is segmented to produce a distance map. An energy function is defined based on the 3D graphs and the distance map. The energy function is minimized to perform non-rigid registration between the 3D image data and the 2D image data. The registration may be optimized.

Abstract: A method for performing deformable non-rigid registration of 2D and 3D images of a vascular structure for assistance in surgical intervention includes acquiring 3D image data. An abdominal aorta is segmented from the 3D image data using graph-cut based segmentation to produce a segmentation mask. Centerlines are generated from the segmentation mask using a sequential topological thinning process. 3D graphs are generated from the centerlines. 2D image data is acquired. The 2D image data is segmented to produce a distance map. An energy function is defined based on the 3D graphs and the distance map. The energy function is minimized to perform non-rigid registration between the 3D image data and the 2D image data. The registration may be optimized.