Abstract: A method for segmenting metal objects in projection images acquired using different projection geometries is provided. Each projection image shows a region of interest. A three-dimensional x-ray image is reconstructed from the projection images in the region of interest. A trained artificial intelligence segmentation algorithm is used to calculate first binary metal masks for each projection image. A three-dimensional intermediate data set of a reconstruction region that is larger than the region of interest is reconstructed by determining, for each voxel of the intermediate data set, as a metal value, a number of first binary metal masks showing metal in a pixel associated with a ray crossing the voxel. A three-dimensional binary metal mask is determined. Second binary metal masks are determined for each projection image by forward projecting the three-dimensional binary metal mask using the respective projection geometries.

Abstract: A method for segmenting metal objects in projection images acquired using different projection geometries is provided. Each projection image shows a region of interest. A three-dimensional x-ray image is reconstructed from the projection images in the region of interest. A trained artificial intelligence segmentation algorithm is used to calculate first binary metal masks for each projection image. A three-dimensional intermediate data set of a reconstruction region that is larger than the region of interest is reconstructed by determining, for each voxel of the intermediate data set, as a metal value, a number of first binary metal masks showing metal in a pixel associated with a ray crossing the voxel. A three-dimensional binary metal mask is determined. Second binary metal masks are determined for each projection image by forward projecting the three-dimensional binary metal mask using the respective projection geometries.