Method for determining a first difference image dataset (DDS-3D, DDS-4D) of an examination volume, wherein the examination volume comprises a vessel (VES.1, VES.2) and wherein the vessel (VES.1, VES.2) contains a contrast agent, comprising: - Receipt (REC-RDS-2D) of two-dimensional real image datasets (RDS-2D.1,..., RDS-2D.4) relating to the examination volume by means of an interface (SYS.IF), wherein each of the two-dimensional real image datasets (RDS-2D) comprises a two-dimensional x-ray projection of the examination volume in relation to a projection direction, wherein the spatial distribution of the contrast agent in the vessel (VES.1, VES.2) differs with different two-dimensional x-ray projections, - Determination (DET-DDS) by means of a processing unit (SYS.CU) of the first difference image dataset (DDS-3D, DDS-4D) based on the two-dimensional real image datasets (RDS-2D.1,..., RDS-2D.4) and based on a first trained function (TF-1, TF-2, TF-3), wherein the first trained function (TF-1, TF-2, TF-3) is applied to input data and in this respect generates output data, wherein the input data is based on the two-dimensional real image datasets (RDS-2D.1,..., RDS-2D.4) and wherein the first difference image dataset (DDS-3D, DDS-4D) is based on the output data, wherein the first difference image dataset (DDS-3D, DDS-4D) is at least three-dimensional, and wherein the first trained function (TF-1, TF-2, TF-3) is based on a neural network, - Determination (DET-DDS') of a four-dimensional second difference image dataset (DDS-4D') based on the three-dimensional first difference image dataset (DDS-3D, DDS-4D) and the two-dimensional real image datasets (RDS-2D.1,..., RDS-2D.4), wherein the four-dimensional second difference image dataset (DDS-4D') is extended with respect to three spatial directions and with respect to a time direction. - Receipt (REC-RDS-2D) of two-dimensional real image datasets (RDS-2D.1,..., RDS-2D.4) relating to the examination volume by means of an interface (SYS.IF), wherein each of the two-dimensional real image datasets (RDS-2D) comprises a two-dimensional x-ray projection of the examination volume in relation to a projection direction, wherein the spatial distribution of the contrast agent in the vessel (VES.1, VES.2) differs with different two-dimensional x-ray projections, - Determination (DET-DDS) by means of a processing unit (SYS.CU) of the first difference image dataset (DDS-3D, DDS-4D) based on the two-dimensional real image datasets (RDS-2D.1,..., RDS-2D.4) and based on a first trained function (TF-1, TF-2, TF-3), - Determination (DET-DDS) by means of a processing unit (SYS.CU) of the first difference image dataset (DDS-3D, DDS-4D) based on the two-dimensional real image datasets (RDS-2D.1,..., RDS-2D.4) and based on a first trained function (TF-1, TF-2, TF-3), wherein the first trained function (TF-1, TF-2, TF-3) is applied to input data and in this respect generates output data, wherein the input data is based on the two-dimensional real image datasets (RDS-2D.1,..., RDS-2D.4) and wherein the first difference image dataset (DDS-3D, DDS-4D) is based on the output data, wherein the first difference image dataset (DDS-3D, DDS-4D) is at least three-dimensional, and wherein the first trained function (TF-1, TF-2, TF-3) is based on a neural network, - Determination (DET-DDS') of a four-dimensional second difference image dataset (DDS-4D') based on the three-dimensional first difference image dataset (DDS-3D, DDS-4D) and the two-dimensional real image datasets (RDS-2D.1,..., RDS-2D.4), - Determination (DET-DDS') of a four-dimensional second difference image dataset (DDS-4D') based on the three-dimensional first difference image dataset (DDS-3D, DDS-4D) and the two-dimensional real image datasets (RDS-2D.1,..., RDS-2D.4), wherein the four-dimensional second difference image dataset (DDS-4D') is extended with respect to three spatial directions and with respect to a time direction.