Iterative algorithm for spatial and intensity normalization of MEMRI images. Application to tract-tracing of rat olfactory pathways

摘要: Manganese (Mn)-enhanced magnetic resonance imaging (MEMRI) is an emerging technique for visualizing neuronal pathways and mapping brain activity modulation in animal models. Spatial intensity normalizations of MEMRI images acquired from different subjects are crucial steps as they can influence the results groupwise analysis. However, no commonly accepted procedure has yet emerged. Here, a normalization method proposed that performs both spatial single iterative process without arbitrary choice reference image. benefit this process. On one hand, increases accuracy region interest (ROI) positioning normalization. other improving leads to better-averaged target on which spatially registered. After automatic fast segmentation optimization process, algorithm revealed presence Mn up posterior entorhinal cortex tract-tracing experiment rat olfactory pathways. Quantitative comparison registration algorithms showed rigid model with anisotropic scaling best deformation intersubject three-dimensional images. Furthermore, errors may occur if ROI chosen intersects regions where concentration differs between experimental groups. Our study suggests cross-comparing Mn-injected animals against Mn-free group provide control avoid bias introduced by quality. It essential optimize detectability local between-group variations directly tied