Background. The brain atrophy observed in patients affected by Alzheimer's disease (AD) is the contribution of a normal aging process plus an AD-specific pathological matter loss. Being able to differentiate these complementary atrophy factors is fundamental to isolate and quantify the pathological AD-related structural changes, and might represent a reliable disgnostic measure, especially at prodromal stages of the disease. We propose a method based on non rigid-registration to identify the brain atrophy component specific to the clinical condition, after extraction and removal of the morphological changes described by the normal aging process. Methods. We chose the structural MRIs for 37 healthy subjects positive to CSF Ab42 (Ab+), 91 MCI converters to AD, 106 MCI non-converters and 134 Alzheimer's patients. For each subject, the normal aging component ("virtual age") has been estimated with respect to the longitudinal deformation modeled for the healthy aging of a group of 63 normal subjects negative to the CSF Ab42. Once removed the aging component, the remaining morphological changes have been analysed group-wise, in order to characterize the atrophy patterns at the different clinical stages. Results. The virtual age estimated with respect to the healthy Ab- longitudinal deformation is shown in Figure 1. Even though the considered groups did not significantly differ for age, the estimated virtual ages significantly increase as the clinical condition get worse. Once removed the healthy aging component, the average morphological changes specific for the clinical groups are shown in Figure 2. The morphological changes specific for the healthy Ab- are mild and mainly located in the frontal lobe, ventricles and entorhinal cortex. The changes specific for the MCI converters are stronger and map to the frontal lobe, ventricles, temporal poles, entorhinal cortex and hippocampus. The same pattern, although more pronounced, is appreciable for the AD patients. Conclusion. We propose a method to decompose the brain atrophy into complementary components: aging and AD specific. These components identify the different clinical stages, and suggest that more advanced AD stages are associated to both "virtually older" brains and increased specific morphological changes that are not related to the normal aging. These results provide new insights that can lead to new understandings of the AD dynamics, and to novel diagnostic techniques for the early detection of the disease. no abstract