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Timothy G. Reese

Researcher at Harvard University

Publications -  110
Citations -  11121

Timothy G. Reese is an academic researcher from Harvard University. The author has contributed to research in topics: Diffusion MRI & Tractography. The author has an hindex of 38, co-authored 107 publications receiving 10447 citations. Previous affiliations of Timothy G. Reese include University of São Paulo & Massachusetts Institute of Technology.

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High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity.

TL;DR: To test whether a geodesic, high b‐value diffusion gradient sampling scheme could resolve multiple fiber orientations within a single voxel, the diffusion signal was modeled as arising from a discrete mixture of Gaussian diffusion processes in slow exchange, and the underlying mixture of tensors was solved for using a gradient descent scheme.
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Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging.

TL;DR: Methods are presented to map complex fiber architectures in tissues by imaging the 3D spectra of tissue water diffusion with MR, showing correspondence between the orientational maxima of the diffusion spectrum and those of the fiber orientation density at each location.
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Reduction of eddy-current-induced distortion in diffusion MRI using a twice-refocused spin echo.

TL;DR: This work presents an improvement on the spin‐echo (SE) diffusion sequence that displays less distortion and consequently improves image quality, and allows more flexible diffusion gradient timing.
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Diffusion MRI of Complex Neural Architecture

TL;DR: The ability of q-ball imaging to resolve complex intravoxel fiber architecture eliminates a key obstacle to mapping neural connectivity in the human brain noninvasively.
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Hyperacute stroke: evaluation with combined multisection diffusion-weighted and hemodynamically weighted echo-planar MR imaging.

TL;DR: Different aspects of hyperacute cerebral ischemia are depicted at DW and HW imaging before infarction is depicted at conventional MR or CT, which may improve stroke diagnosis and may contribute to advances in treatment.