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 required to normalize and compare a region of interest and global brain. Intensity based registration method matches the global brain well. But a region of interest may not be locally normalized compared to feature based method. The method of this paper uses feature similarities of local region as well as intensity similarities. The lateral ventricle and the central gray nuclei of brain including the corpus callosum, which is used for features in Schizophrenia detection, is appropriately normalized. In the results section, our method reduces the difference of feature area such as corpus callosum (7.7%, 2.4%) and lateral ventricle (8.2%, 13.5%) compared with mutual information and Talairach methods.
Kim
June-Sic
JS
Department of Biomedical Engineering, Hanyang University, Sungdong P.O. Box 55, Seoul 133-605, South Korea.
Lee
Jong-Min
JM
Lee
Yong-Hee
YH
Kim
Jae-Seok
JS
Kim
In-Young
IY
Kim
Sun I
SI
D000465:Algorithms; D001921:Brain / Q000473:pathology*; D001931:Brain Mapping; D002540:Cerebral Cortex / Q000473:pathology; D003337:Corpus Callosum / Q000473:pathology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional; D016014:Linear Models; D008279:Magnetic Resonance Imaging; D012016:Reference Values; D012559:Schizophrenia / Q000175:diagnosis* / Q000473:pathology; D012984:Software; D013687:Telencephalon / Q000473:pathology; D013698:Templates, Genetic