Abstract: A method is disclosed for providing a virtual tomographic stroke follow-up examination image. In an embodiment, the method includes: receiving a sequence of temporally successive tomographic perfusion imaging data sets of a region for examination; calculating the virtual tomographic stroke follow-up examination image of the region for examination by applying a trained machine learning algorithm to the sequence of temporally successive tomographic perfusion imaging data sets received; and providing the virtual tomographic stroke follow-up examination image calculated.

Abstract: A method is disclosed for providing an optimized energy bin parameter set for photon-counting spectral computed tomography. In one embodiment, the method includes receiving photon-counting spectral computed tomography data related to a plurality of energy bins and an initial energy bin parameter set; and performing iteration steps of a plurality of iteration steps. An input of the first iteration step of the plurality of iteration steps includes the initial energy bin parameter set as an input energy bin parameter set and the input of each further iteration step of the plurality of iteration steps includes an adjusted energy bin parameter set calculated in the preceding iteration step of the plurality of iteration steps as the input energy bin parameter set.

Abstract: A method is disclosed for providing an optimized energy bin parameter set for photon-counting spectral computed tomography. In one embodiment, the method includes receiving photon-counting spectral computed tomography data related to a plurality of energy bins and an initial energy bin parameter set; and performing iteration steps of a plurality of iteration steps. An input of the first iteration step of the plurality of iteration steps includes the initial energy bin parameter set as an input energy bin parameter set and the input of each further iteration step of the plurality of iteration steps includes an adjusted energy bin parameter set calculated in the preceding iteration step of the plurality of iteration steps as the input energy bin parameter set.

Abstract: A method is disclosed for providing a virtual tomographic stroke follow-up examination image. In an embodiment, the method includes: receiving a sequence of temporally successive tomographic perfusion imaging data sets of a region for examination; calculating the virtual tomographic stroke follow-up examination image of the region for examination by applying a trained machine learning algorithm to the sequence of temporally successive tomographic perfusion imaging data sets received; and providing the virtual tomographic stroke follow-up examination image calculated.