A method for non-invasively classifying a tumorous modification of a tissue according to different stages of the tumorous modification comprises the steps of: a) receiving raw magnetic resonance imaging (MRI) data that has been recorded by applying at least one diffusion weighted imaging (DWI) sequence using three to nine different b-values to a tissue being suspicious to a tumorous modification without application of a contrast agent； b) extracting at least two quantification scheme parameters from the raw MRI data by using at least one quantification scheme, wherein each of the quantification scheme parameters is related to a microstructural property of the tissue； c) applying a weight to each quantification scheme parameter, wherein the weight is dependent on a kind of the tissue and on the quantification scheme, whereby a set of weighted quantification scheme parameters is obtained； d) determining a scoring value by combining the weighted quantification scheme parameters within the set, wherein each of the weighted quantification scheme parameters is used only once for determining the scoring value； and e) classifying the tumorous modification of the tissue into one of at least two classes according to the scoring value. The method and a corresponding classification device are capable of performing non-invasive tissue characterization without contrast agent administration in a highly accurate manner while supplementary information related to conventional imaging properties and clinical information can further increase the high diagnostic accuracy. They are used in their entirety for classifying the tumorous modification of the tissue.L'invention concerne un procédé de classification non invasive d'une modification tumorale d'un tissu selon différents stades de la modification tumorale, qui comprend les étapes consistant à : a) recevoir des données d'imagerie par résonance magnétique (IRM) brutes qui ont été enregistrées en appliquant au moins une séquence d'imag
