Ning Kang

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Senior Programmer
B.S./M.S. Mechanical (Thermal) Engineering, Chongqing University, China
M.S. Computer Science, North Carolina State University
Ph.D. Computer Science, University of Kentucky

Research Interests
My research specialty is in fiber tractography, which is based on the anisotropic diffusion simulations. Fiber tracking schemes can be used to examine the pathways of white matter tracts, quantify the white matter in the brain, and help identify white matter diseases (Multiple Sclerosis (MS), Alzheimer, stroke, chronic alcohol, Amyotrophic Lateral Sclerosis (ALS), and others). Since the efficiency of cognitive is highly dependent on the integrity of white matter pathways, fiber tractography is a novel technique in examining specific type of fibers that can potentially damage overall cognitive abilities. My goal is to improve the diffusion simulation-based fiber tractography such that it can accommodate the HARDI data technique.

Research Projects

As a programmer, I am involved in developing, improving, and adding more functions to the AFNI diffusion plug-in and the diffusion simulation-based fiber tractography (DST). I am also developing tools to facilitate the calculation of foliation in different species of sharks and human brains.

Publications
Ning Kang, Jun Zhang, Eric S. Carlson, and Daniel Gembris. 2005. White matter fiber tractography via anisotropic diffusion simulation in the human brain, IEEE Transactions on Medical Imaging, Vol. 24 (9), pp. 1127-1137.

Jun Zhang, Ning Kang, and Stephen E. Rose. 2005. Approximating anatomical brain connectivity with diffusion tensor MRI using kernel-based diffusion simulations, Proceedings of the 19th Conference on Information Processing in Medical Imaging (IPMI 2005), G.E. Christensen and M. Sonka (Eds.), LNCS 3565, pp. 64-75.

Ning Kang, Jun Zhang, and Eric S. Carlson. 2005. Fiber tracking by simulating diffusion process with diffusion kernels in human brain with DT-MRI data, Proceedings of SPIE on Physiology, Function, and Structure from Medical Images, A.A. Amini and A. Manducs (Eds.), Vol. 5746, pp. 126-137.

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