3D mouse brain reconstruction from histology using a coarse-to-fine approach

Authors:
Paul A. Yushkevich;Brian B. Avants;Lydia Ng;Michael Hawrylycz;Pablo D. Burstein;Hui Zhang;James C. Gee
Affiliations:
Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA;Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA;Allen Institute for Brain Science, Seattle, WA;Allen Institute for Brain Science, Seattle, WA;Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA;Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA;Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA
Venue:
WBIR'06 Proceedings of the Third international conference on Biomedical Image Registration
Year:
2006

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Abstract

The Allen Brain Atlas project aims to bridge the divide between genomics and neuroanatomy by mapping the expression of the entire C57BL/6J mouse genome onto a high-resolution 3D anatomical reference atlas of the mouse brain. We present the image registration approach used to generate this anatomical reference from histological sections. Due to the large number of sections (525) and the presence of debris and distortions, a straightforward alignment of each slice to its neighbors fails to accurately recover the 3D shape of the brain. On the other hand, multimodality registration of histology slices to an MRI reference compromises correspondences between neighboring slices. Our approach combines the high-frequency component of slice-to-slice histology registration with the low-frequency component of the histology-to-MRI registration to produce a coarse-to-fine reconstruction that is accurate both in its global shape and in the alignment of local features.