Brain Connectivity Mapping Using Riemannian Geometry, Control Theory, and PDEs

DOI10.1137/070710986zbMath1181.68294OpenAlexW1976470854WikidataQ115247125 ScholiaQ115247125MaRDI QIDQ3183389

J.-P. Pons, Olivier Faugeras, Emmanuel Prados, Rachid Deriche, Christophe Lenglet

Publication date: 19 October 2009

Published in: SIAM Journal on Imaging Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/070710986

zbMATH Keywords

Brownian motionRiemannian manifoldsdiffusion processHamilton-Jacobi-Bellman equationslevel setcontrol theorypartial differential equationsdiffusion tensor imagingfast marching methodsanisotropic eikonal equationintrinsic distance functionbrain connectivity mapping

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Biomedical imaging and signal processing (92C55) Computer graphics; computational geometry (digital and algorithmic aspects) (68U05) Existence theories for optimal control problems involving partial differential equations (49J20)

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Adjugate diffusion tensors for geodesic tractography in white matter ⋮ Riemann-DTI Geodesic Tractography Revisited ⋮ Equivalent extensions of Hamilton-Jacobi-Bellman equations on hypersurfaces ⋮ Morphological and linear scale spaces for fiber enhancement in DW-MRI ⋮ Optimal paths for variants of the 2D and 3D Reeds-Shepp car with applications in image analysis ⋮ Equivalent extensions of partial differential equations on surfaces

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