Truly 3D midsagittal plane extraction for robust neuroimage registration

This paper describes a robust algorithm for reliable ideal midsagittal plane extraction (iMSP) from 3D neuroimages. The algorithm makes no assumptions about initial orientation of a given 3D brain image and works reliably on neuroimages of normal brains as well as brains with significant pathologies. Presented technique is truly three-dimensional since we treat each neuroimage as a three-dimensional volume rather than a set of two-dimensional slices. We use an edge-based approach which employs cross-correlation to extract iMSP. Proposed algorithm was quantitatively evaluated on a variety of real and artificial neuroimages. We find that our algorithm is able to extract iMSP from neuroimages with arbitrary initial orientations, large asymmetries, and low signal to noise ratio. We also demonstrate that presented algorithm can increase robustness of existing neuroimage registration algorithms, be it rigid, affine or less restricted deformable registration. Our algorithm was implemented using Insight Toolkit(ITK)