document: Intensity based affine registration including feature similarity for spatial normalization This paper presents a new spatial normalization with affine transformation . The quantitative comparison of brain architecture across different subjects requires a common coordinate system . For the analysis of a specific brain area , it is necessary to normalize and compare a region of interest and the global brain . The intensity based registration method matches the global brain well , but a region of interest may not be locally normalized compared to the feature based method . The method in this paper uses feature similarities of local regions as well as intensity similarities . The lateral ventricle and central gray nuclei of the brain , including the corpus callosum , which is used for features in schizophrenia detection , is appropriately normalized . Our method reduces the difference of feature areas such as the corpus callosum -LRB- 7.7 % , 2.4 % -RRB- and lateral ventricle -LRB- 8.2 % , 13.5 % -RRB- compared with mutual information and Talairach methods
doc_bio_tags: B I I I O B I O B I O O O O O B I O B I O O O O O B I O O O O O B I I O O O O O O O O O O O O O O O O O O B I I O O B I O O O O O O O O B I O O O O B I I O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O B I O B I I O O O O O O B I O O O O O O O B I O O O O O O O O O O O O O O O O B I O O O O O O O O B I O O O O O O O O O O O O O O
extractive_keyphrases: intensity based affine registration feature similarity spatial normalization affine transformation brain architecture common coordinate system global brain region of interest feature similarities lateral ventricle central gray nuclei corpus callosum schizophrenia detection
abstractive_keyphrases: mutual information method talairach method