If substantial differences are detected between one or more acquired signals and the reference spectral models, these samples are identified, classified as unreliable and automatically discarded: for instance, spectra which are not clearly associated to bone portions but to osteophytes or calcifications. Hence, this approach natively identifies and eliminates outliers, bringing significant advantages with respect to the clinical reliability of the obtained results.