Technical Program

Paper Detail

Paper:	SA-AM-OS4.4
Session:	Diffusion Tensor Imaging
Time:	Saturday, April 8, 12:10 - 12:30
Presentation:	Oral
Title:	A Diffusion Tensor Imaging Tractography Method Based on Navier-Stokes Fluid Mechanics
Authors:	Nathan Hageman; UCLA School of Medicine
	David Shattuck; UCLA School of Medicine
	Katherine Narr; UCLA School of Medicine
	Arthur W. Toga; UCLA School of Medicine
Abstract:	We introduce a method for estimating regional connectivity in diffusion tensor magnetic resonance imaging (DT-MRI) based on a fluid mechanics model. We customize the Navier-Stokes equations to include information from the diffusion tensor and simulate an artificial fluid flow. The velocity vector field of this fluid construct is then used as a connectivity metric. We tested our algorithm on a digital DTI phantom. Our method was able to correctly segment the structure of the phantom with various levels of noise, despite local distortion of the image pattern. We applied our method to DTI volumes from a normal human subject. Our method produced paths that were consistent with both known anatomy and directionally encoded color (DEC) images of the DTI volumes.

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