Jonathan A. D. Farrell
Radiology, Nuclear Medicine and Imaging · 2007–2010
A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Radiology, Nuclear Medicine and Imaging — 27 citations into it
- Orthopedics and Sports Medicine — 5 citations into it
Whom Jonathan A. D. Farrell trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Jonathan A. D. Farrell's perspective
Ordered by how strongly the researchers Jonathan A. D. Farrell trusts endorse each paper. Same corpus, a different order for every researcher.
- Condition number as a measure of noise performance of diffusion tensor data acquisition schemes with MRI. (Journal of magnetic resonance (San Diego, Calif. 1997 : Print))
- Characterization of anisotropy in high angular resolution diffusion‐weighted MRI (Magnetic Resonance in Medicine)
- The effect of gradient sampling schemes on measures derived from diffusion tensor MRI: A Monte Carlo study † (Magnetic Resonance in Medicine)
- Determining and visualizing uncertainty in estimates of fiber orientation from diffusion tensor MRI (Magnetic Resonance in Medicine)
- How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging (NeuroImage)
- Image‐based method for retrospective correction of physiological motion effects in fMRI: RETROICOR (Magnetic Resonance in Medicine)
- Medial prefrontal cortex and self-referential mental activity: Relation to a default mode of brain function (Proceedings of the National Academy of Sciences of the United States of America)
- Actual flip‐angle imaging in the pulsed steady state: A method for rapid three‐dimensional mapping of the transmitted radiofrequency field (Magnetic Resonance in Medicine)
- Functional connectivity in the resting brain: A network analysis of the default mode hypothesis (Proceedings of the National Academy of Sciences of the United States of America)
- Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images (NeuroImage)