Abstract #2906

Assessment of SPM5s Brain Registration Performance Using Landmark Points

Joao Miguel Pereira¹, Guy B. Williams¹, Li Xiong^2,3, Julio Acosta-Cabronero¹, George Pengas², Peter J. Nestor²

¹Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK; ²Clinical Neurosciences, University of Cambridge, Cambridge, UK; ³Neurology Department, Wuhan University, Wuhan, China

The performance of registration algorithms is known to be one of the limiting factors of automated morphology methods. One such technique is voxel based morphometry (VBM), which is used to detect structural changes in diseased cohorts by contrasting them with healthy subjects this is highly dependent on the performance of the registration step. The goal of this study was to quantify the misregistration of well characterised landmark points using standard SPM5 tools in both normal and diseased cohorts. Results showed that the standard unified segmentation and more complex methods such as DARTEL yield comparable results.