Multiscale image and multiscale deformation of brain anatomy for building average brain atlases

In this work we consider the process of aligning a set of anatomical MRI scans, from a group of subjects, to a single reference MRI scan as accurately as possible. A key requirement of this anatomical normalization is the ability to bring into alignment brain images with different ages and disease states with equal accuracy and precision, enabling the unbiased comparison of different groups. Typical images of such anatomy may vary in terms of both tissue shape, location and contrast. To address this we have developed, a highly localized free-form inter-subject registration algorithm driven by normalized mutual information. This employs an efficient multi-image resolution and multi-deformation resolution registration procedure. In this paper we examine the behavior of this algorithm when applied to aligning high-resolution MRI of groups of younger, older and atrophied brain anatomy to different target anatomies. To gain an insight into the quality of the spatial normalization, we have examined two properties of the transformations: The residual intensity differences between spatially normalized MRI values and the spatial discrepancies in transformation estimates between group and reference, derived from transformations between 168 different image pairs. These are examined with respect to the coarseness of the deformation model employed.

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