1. A method for automatically detecting at least one of chemical anomalies and salient features in soft tissue of an object area, wherein two computed tomography pictures of an object area are recorded in the context of a different spectral distribution of the X-radiation, and, from raw data of the two computed tomography pictures, two image data records of the object area are reconstructed that include X-ray attenuation values of voxels on the object area in the context of the respective spectral distribution of the X-radiation, the method, for at least a portion of the voxels of at least one interesting slice of the object area whose mean value from the two assigned X-ray attenuation values of the two image data records lies within a prescribed value range, comprising: determining a data point of the voxel in a diagram, in which X-ray attenuation values are plotted against one another in the context of two spectral distributions of the X-radiation, at least one of from the two X-ray attenuation values of the voxel and from two averaged X-ray attenuation values that are obtained by averaging the X-ray attenuation values of voxels inside a prescribed volume around the voxel in the respective image data record; calculating a perpendicular distance of the data point of the voxel from a connecting straight line that connects prescribed data points for pure fat and for pure soft tissue in the diagram; and marking and highlighting the voxel when the calculated distance exceeds a prescribed value for the distance.