Ben Jeurissen

Radiology, Nuclear Medicine and Imaging · 2009–2019

A researcher in the Science corpus: 9 papers; trusts 27 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

Whom Ben Jeurissen trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Jacques-Donald Tournier
  2. Alexander Leemans
  3. Derek K. Jones
  4. David S. Tuch
  5. Fernando Calamante
  6. Maxime Descoteaux
  7. Alan Connelly
  8. Timothy Edward John Behrens
  9. Rowan J. Smith
  10. Peter J. Basser

Who trusts Ben Jeurissen overall

  1. Alexander Leemans
  2. Jacques-Donald Tournier
  3. Jelle Veraart
  4. Saâd Jbabdi
  5. Maxime Descoteaux
  6. Jakob Wasserthal
  7. Derek K. Jones
  8. Jan Sijbers
  9. Eleftherios Garyfallidis
  10. David A. Raffelt

Papers from Ben Jeurissen's perspective

Ordered by how strongly the researchers Ben Jeurissen trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Q‐ball imaging (Magnetic Resonance in Medicine)
  2. In vivo fiber tractography using DT‐MRI data (Magnetic Resonance in Medicine)
  3. Characterization and propagation of uncertainty in diffusion‐weighted MR imaging (Magnetic Resonance in Medicine)
  4. Virtual in Vivo Interactive Dissection of White Matter Fasciculi in the Human Brain (NeuroImage)
  5. Resolution of complex tissue microarchitecture using the diffusion orientation transform (DOT) (NeuroImage)
  6. Robust determination of the fibre orientation distribution in diffusion MRI: Non-negativity constrained super-resolved spherical deconvolution (NeuroImage)
  7. Diffusion Tensor Imaging and Beyond (Magnetic Resonance in Medicine)
  8. Composite hindered and restricted model of diffusion (CHARMED) MR imaging of the human brain (NeuroImage)
  9. Deterministic and Probabilistic Tractography Based on Complex Fibre Orientation Distributions (IEEE Transactions on Medical Imaging)
  10. Probabilistic diffusion tractography with multiple fibre orientations: What can we gain? (NeuroImage)

Their papers