A computer-implemented method for providing a classification explanation, comprising: - receiving (REC-IMG.A) an acquired medical image (IMG.A) corresponding to an examination volume, - receiving or determining (REC-DET-CV.A) an actual classification value (CV.A), wherein the actual classification value (CV.A) classifies an anatomical structure within the acquired medical image (IMG.A), - receiving or determining (REC-DET-CV.1) a first classification value (CV.1) being different from the actual classification value (CV.A), wherein the first classification value (CV.1) is a potential classification value related to a classification of the anatomical structure within the acquired medical image (IMG.A), wherein the anatomical structure within the acquired medical image (IMG.A) is a lesion, wherein the actual classification value (CV.A) and the first classification value (CV.1) correspond to a benignancy and/or a malignancy of the lesion, - applying (APPL-GF.1) a first generative function (GF.1) to the acquired medical image (IMG.A), thereby generating a first synthetic image (IMG.S1), wherein the first generative function (GF.1) is configured to modify the anatomical structure to exhibit the first classification value (CV.1), - providing (PROV-VIS) a visualization based on the acquired medical image (IMG.A) and the first synthetic image (IMG.S1), characterized in that the first classification value (CV.1) is used as an input parameter for the first generative function (GF.1). - receiving (REC-IMG.A) an acquired medical image (IMG.A) corresponding to an examination volume, - receiving or determining (REC-DET-CV.A) an actual classification value (CV.A), wherein the actual classification value (CV.A) classifies an anatomical structure within the acquired medical image (IMG.A), - receiving or determining (REC-DET-CV.1) a first classification value (CV.1) being different from the actual classification value (CV.A), wherein the first classification value (CV.1) is a potential classification value related to a classification of the anatomical structure within the acquired medical image (IMG.A), wherein the anatomical structure within the acquired medical image (IMG.A) is a lesion, wherein the actual classification value (CV.A) and the first classification value (CV.1) correspond to a benignancy and/or a malignancy of the lesion, wherein the first classification value (CV.1) is a potential classification value related to a classification of the anatomical structure within the acquired medical image (IMG.A), wherein the anatomical structure within the acquired medical image (IMG.A) is a lesion, wherein the actual classification value (CV.A) and the first classification value (CV.1) correspond to a benignancy and/or a malignancy of the lesion, - applying (APPL-GF.1) a first generative function (GF.1) to the acquired medical image (IMG.A), thereby generating a first synthetic image (IMG.S1), wherein the first generative function (GF.1) is configured to modify the anatomical structure to exhibit the first classification value (CV.1), - providing (PROV-VIS) a visualization based on the acquired medical image (IMG.A) and the first synthetic image (IMG.S1), <EOS>