Tensor Visualization for Finding Structures in Brain and Nematic Liquid Crystal

	Special Guest Lectures
	Tensor Visualization for Finding Structures in Brain and Nematic Liquid Crystal
	Song Zhang, Mississippi State University
	Assistant Professor, Department of Computer Science and Engineering
	Johnston Hall 338 May 15, 2007 - 03:30 pm
Abstract: Matrix-valued datasets (so-called tensor field) have become more common in various disciplines of science. Compared to scalar dataset or vector field, tensor field incorporates more information at any one data point. New visualization and analysis tools are necessary. In this talk, I will give an overview of tensor visualization in two areas: diffusion tensor imaging and nematic liquid crystal simulation. Diffusion tensor imaging (DTI) is a 3D imaging method that yields a diffusion tensor in each voxel. This diffusion tensor describes the diffusive behavior of water molecules in the tissue. Nematic liquid crystal simulation yields a Q tensor in each voxel that describes the aggregate behavior of a group of molecules. I will present our work in reconstructing and visualizing neural fibers in the white matter from DTI and detecting defects in nematic liquid crystal.

Speaker's Bio: Dr. Song Zhang is an assistant professor of computer science and engineering within the James Worth Bagley College of Engineering, Mississippi State University. His research areas include Scientific visualization, data analysis, medical imaging and computer graphics. Song has a Master's and Ph.D. from Brown University and a B.S. from Nankai University.

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