Method for determining at least one diffusion parameter for a person under examination using MR signals, comprising the following steps: - acquiring MR signals in a plurality of diffusion measurements, wherein each diffusion measurement is measured using a defined set of MR parameters, wherein the plurality of diffusion measurements differ amongst each other in terms of at least one MR parameter, thereby creating a measured MR-signal dataset, which comprises the MR signals for the different MR parameters used, wherein a plurality of MR diffusion images are generated from the MR signals, for which images the signal intensity over time in the individual pixels of the MR diffusion images is considered in order to create a measured MR-signal data vector (36a - 36d) for each pixel, wherein the measured MR-signal data vector comprises the measured signal intensities for the different MR parameters used, which were employed in the various diffusion measurements; - determining a multiplicity of calculated datasets using a predetermined diffusion model, wherein the diffusion model describes the change in the MR signals for the diffusion measurements carried out, and a defined number of different model parameters is used for all the calculated datasets, wherein for different values of the model parameters and each combination of the different model parameter values, there exists a calculated MR-signal intensity for the diffusion measurements; - comparing the measured MR-signal dataset with the multiplicity of the calculated datasets in order to identify the calculated dataset that, on the basis of a quality criterion, has the closest match to the measured MR-signal dataset; - determining the at least one diffusion parameter from the calculated dataset having the closest match, wherein the at least one diffusion parameter is determined from the model parameters that were used in determining the calculated dataset having the closest match, characterised in that in the plurality of diffusion measurements, in each case the associated raw data space is fully sampled in accordance with the Nyquist condition. - acquiring MR signals in a plurality of diffusion measurements, wherein each diffusion measurement is measured using a defined set of MR parameters, wherein the plurality of diffusion measurements differ amongst each other in terms of at least one MR parameter, thereby creating a measured MR-signal dataset, which comprises the MR signals for the different MR parameters used, wherein a plurality of MR diffusion images are generated from the MR signals, for which images the signal intensity over time in the individual pixels of the MR diffusion images is considered in order to create a measured MR-signal data vector (36a - 36d) for each pixel, wherein the measured MR-signal data vector comprises the measured signal intensities for the different MR parameters used, which were employed in the various diffusion measurements; - determining a multiplicity of calculated datasets using a predetermined diffusion model, wherein the diffusion model describes the change in the MR signals for the diffusion measurements carried out, and a defined number of different model parameters is used for all the calculated datasets, wherein for different values of the model parameters and each combination of the different model parameter values, there exists a calculated MR-signal intensity for the diffusion measurements; - comparing the measured MR-signal dataset with the multiplicity of the calculated datasets in order to identify the calculated dataset that, on the basis of a quality criterion, has the closest match to the measured MR-signal dataset; - determining the at least one diffusion parameter from the calculated dataset having the closest match, wherein the at least one diffusion parameter is determined from the model parameters that were used in determining the calculated dataset having the closest match, characterised in that in the plurality of diffusion measurements, in each case the associated raw data space is fully sampled in accordance with the Nyquist condition.