A computer-implemented method of estimating a convective velocity v and a dispersion coefficient D of a contrast agent, the method comprising: - receiving a plurality of video frames that were produced using a dynamic contrast enhanced imaging process, each video frame comprising a plurality of pixels/voxels; - defining a local kernel, the local kernel comprising a number of neighboring pixels/voxels; - placing the local kernel at a first location in each video frame; - determining indicator-dilution curves for the pixels/voxels in the local kernel using the received plurality of video frames; - comparing the indicator-dilution curves between two of a pair of pixels/voxels for a number of pairs of pixels/voxels within the local kernel to obtain a spatiotemporal dependency of the concentration evolution between the pixels/voxels within the local kernel; - repeating the step of comparing the indicator-dilution curves after having relocated the local kernel, until no relocation of the local kernel is needed; - estimating the velocity for at least some of the pixels/voxels of the video frames using the spatiotemporal dependency; - rendering the estimated velocity in a 2D or 3D image, wherein the step of estimating the velocity comprises: - determining a convection-diffusion model using the spatiotemporal dependency, wherein the convection-diffusion model is chosen to be parameterized by two parameters v and D, the parameter v being the convective velocity v of the convection diffusion model and the parameter D being the dispersion coefficient D of the convection-diffusion model; - solving the convection-diffusion model in the chosen parameterization to obtain its parameters v and D, the convective velocity v and dispersion coefficient D. - receiving a plurality of video frames that were produced using a dynamic contrast enhanced imaging process, each video frame comprising a plurality of pixels/voxels; - defining a local kernel, the local kernel comprising a number of neighboring pixels/voxels; - placing the local kernel at a first location in each video frame; - determining indicator-dilution curves for the pixels/voxels in the local kernel using the received plurality of video frames; - comparing the indicator-dilution curves between two of a pair of pixels/voxels for a number of pairs of pixels/voxels within the local kernel to obtain a spatiotemporal dependency of the concentration evolution between the pixels/voxels within the local kernel; - repeating the step of comparing the indicator-dilution curves after having relocated the local kernel, until no relocation of the local kernel is needed; - estimating the velocity for at least some of the pixels/voxels of the video frames using the spatiotemporal dependency; - rendering the estimated velocity in a 2D or 3D image, wherein the step of estimating the velocity comprises: - determining a convection-diffusion model using the spatiotemporal dependency, wherein the convection-diffusion model is chosen to be parameterized by two parameters v and D, the parameter v being the convective velocity v of the convection diffusion model and the parameter D being the dispersion coefficient D of the convection-diffusion model; - solving the convection-diffusion model in the chosen parameterization to obtain its parameters v and D, the convective velocity v and dispersion coefficient D.