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Abstract #3270

The Effect of Diffusion Tensor Imaging SNR on Skeletal Muscle Tractography

Armen Alex Gharibans1, Curtis Laurence Johnson1, Danchin Daniel Chen1, John G. Georgiadis1

1Mechanical Science & Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States


Since skeletal muscle DTI has relatively low SNR, the choice of the tractography method and minimum SNR required should be important parameters in the design of any DTI protocol for skeletal muscle, if the results are to be compared across subjects and scanners. This work is focused on studying the effect of DTI SNR on tractography in skeletal muscle by comparing the convergence of a number of geometrical tract characteristics for four deterministic tracking algorithms. As an indication, the interpolated streamline method converged at SNR~15, Tensorline and Runge-Kutta at SNR~20, and FACT at SNR~40.

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