Slice-to-Volume Nonrigid Registration of Histological Sections to MR Images of the Human Brain
Author(s) -
Sergey Osechinskiy,
Frithjof Kruggel
Publication year - 2010
Publication title -
anatomy research international
Language(s) - English
Resource type - Journals
eISSN - 2090-2751
pISSN - 2090-2743
DOI - 10.1155/2011/287860
Subject(s) - image registration , artificial intelligence , computer science , volume (thermodynamics) , computer vision , spline (mechanical) , magnetic resonance imaging , rigid transformation , thin plate spline , pattern recognition (psychology) , medicine , radiology , image (mathematics) , physics , structural engineering , quantum mechanics , engineering , bilinear interpolation , spline interpolation
Registration of histological images to three-dimensional imaging modalities is an important step in quantitative analysis of brain structure, in architectonic mapping of the brain, and in investigation of the pathology of a brain disease. Reconstruction of histology volume from serial sections is a well-established procedure, but it does not address registration of individual slices from sparse sections, which is the aim of the slice-to-volume approach. This study presents a flexible framework for intensity-based slice-to-volume nonrigid registration algorithms with a geometric transformation deformation field parametrized by various classes of spline functions: thin-plate splines (TPS), Gaussian elastic body splines (GEBS), or cubic B-splines. Algorithms are applied to cross-modality registration of histological and magnetic resonance images of the human brain. Registration performance is evaluated across a range of optimization algorithms and intensity-based cost functions. For a particular case of histological data, best results are obtained with a TPS three-dimensional (3D) warp, a new unconstrained optimization algorithm (NEWUOA), and a correlation-coefficient-based cost function
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