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

intensity normalization. On the other hand, improving the intensity normalization of the different MEMRI images leads to a better-averaged target on which the images are spatially registered. After automatic fast brain segmentation and optimization of the normalization process, this algorithm revealed the presence of Mn up to the posterior entorhinal cortex in a tract-tracing experiment on rat olfactory pathways. Quantitative comparison of registration algorithms showed that a rigid model with anisotropic scaling is the best deformation model for intersubject registration of three-dimensional MEMRI images. Furthermore, intensity normalization errors may occur if the ROI chosen for intensity normalization intersects regions where Mn concentration differs between experimental groups. Our study suggests that cross-comparing Mn-injected animals against a Mn-free group may provide a control to avoid bias introduced by intensity normalization quality. It is essential to optimize spatial and intensity normalization as the detectability of local between-group variations in Mn concentration is directly tied to normalization quality.

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Additional Info

Field Value
Source ISSN: 0730-725X
Author Lehallier, Benoît, B., Andrey, Philippe, P., Maurin, Yves, Y., Bonny, J.-M.
Maintainer CCSD
Last Updated May 7, 2026, 04:22 (UTC)
Created May 7, 2026, 04:22 (UTC)
Identifier hal-00939838
Language en
contributor Qualité des Produits Animaux (QuaPA) ; Institut National de la Recherche Agronomique (INRA)
creator Lehallier, Benoît, B.
date 2011-05-07T00:00:00
harvest_object_id c438e455-7ba3-4830-a032-fe9abf55b0e3
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2025-03-21T00:00:00
relation info:eu-repo/semantics/altIdentifier/doi/10.1016/j.mri.2011.07.014
set_spec type:ART