Title :
Shape-Based Normalization of the Corpus Callosum for DTI Connectivity Analysis
Author :
Sun, Hui ; Yushkevich, Paul A. ; Zhang, Hui ; Cook, Philip A. ; Duda, Jeffrey T. ; Simon, Tony J. ; Gee, James C.
Author_Institution :
Pennsylvania Univ., Philadelphia
Abstract :
The continuous medial representation (cm-rep) is an approach that makes it possible to model, normalize, and analyze anatomical structures on the basis of medial geometry. Having recently presented a partial differential equation (PDE)-based approach for 3-D cm-rep modeling [1], here we present an equivalent 2-D approach that involves solving an ordinary differential equation. This paper derives a closed form solution of this equation and shows how Pythagorean hodograph curves can be used to express the solution as a piecewise polynomial function, allowing efficient and robust medial modeling. The utility of the approach in medical image analysis is demonstrated by applying it to the problem of shape-based normalization of the midsagittal section of the corpus callosum. Using diffusion tensor tractography, we show that shape- based normalization aligns subregions of the corpus callosum, defined by connectivity, more accurately than normalization based on volumetric registration. Furthermore, shape-based normalization helps increase the statistical power of group analysis in an experiment where features derived from diffusion tensor tractography are compared between two cohorts. These results suggest that cm-rep is an appropriate tool for normalizing the corpus callosum in white matter studies.
Keywords :
biomedical MRI; brain; differential equations; image representation; medical image processing; network theory (graphs); 2D cm-rep; DTI connectivity analysis; Pythagorean hodograph curves; anatomical structure analysis; anatomical structure modeling; anatomical structure normalization; continuous medial representation; corpus callosum midsagittal section; diffusion tensor tractography; group analysis; medial anatomical structure geometry; medical image analysis; ordinary differential equation; piecewise polynomial function; shape based corpus callosum normalization; Anatomical structure; Closed-form solution; Differential equations; Diffusion tensor imaging; Geometry; Partial differential equations; Polynomials; Robustness; Solid modeling; Tensile stress; Corpus callosum; geometrical representation; image analysis; medial; medial representation; shape analysis; skeleton; Algorithms; Artificial Intelligence; Child; Computer Simulation; Corpus Callosum; Diffusion Magnetic Resonance Imaging; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Models, Neurological; Models, Statistical; Nerve Fibers, Myelinated; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Subtraction Technique;
Journal_Title :
Medical Imaging, IEEE Transactions on
DOI :
10.1109/TMI.2007.900322