A systematic characterization of the similarities and differences among different methods for detecting structural brain abnormalities in schizophrenia,such as voxel-based morphometry (VBM),tensor-based morphometry (TBM),and projection-based thickness (PBT),is important for understanding the brain pathology in schizophrenia and for developing effective biomarkers for a diagnosis of schizophrenia.However,such studies are still lacking.Here,we performed VBM,TBM,and PBT analyses on T1-weighted brain MR images acquired from 116 patients with schizophrenia and 116 healthy controls.We found that,although all methods detected wide-spread structural changes,different methods captured different information-only 10.35% of the grey matter changes in cortex were detected by all three methods,and VBM only detected 11.36% of the white matter changes detected by TBM.Further,pattern classification between patients and controls revealed that combining different measures improved the classification accuracy (81.9%),indicating that fusion of different structural measures serves as a better neuroimaging marker for the objective diagnosis of schizophrenia.