Filtered Tractography: Validation on a Physical Phantom
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Author(s)
Malcolm, James G.
Shenton, Martha E.
Rathi, Yogesh
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Abstract
This note summarizes a technique that uses tractography to drive the
local fiber model estimation. Existing techniques use independent estimation at
each voxel so there is no running knowledge of confidence in the estimated model
fit. We formulate fiber tracking as recursive estimation: at each step of tracing
the fiber, the current estimate is guided by the previous. To do this we perform
tractography within a filter framework and use a discrete mixture of Gaussian
tensors to model the signal. Starting from a seed point, each fiber is traced to its
termination using an unscented Kalman filter to simultaneously fit the local model
to the signal and propagate in the most consistent direction. Despite the presence
of noise and uncertainty, this provides a causal estimate of the local structure
at each point along the fiber. We applied this technique to a phantom simulating
several complex pathway interactions and highlight tracts passing through several
prescribed seed positions.
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2009-09-24
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Proceedings