Harvard Catalyst Profiles

Contact, publication, and social network information about Harvard faculty and fellows.

Simon Keith Warfield, Ph.D.

Co-Author

This page shows the publications co-authored by Simon Warfield and Maxime Taquet.
Connection Strength

5.577
  1. Improved fidelity of brain microstructure mapping from single-shell diffusion MRI. Med Image Anal. 2015 Dec; 26(1):268-86.
    View in: PubMed
    Score: 0.661
  2. A fully Bayesian inference framework for population studies of the brain microstructure. Med Image Comput Comput Assist Interv. 2014; 17(Pt 1):25-32.
    View in: PubMed
    Score: 0.583
  3. A mathematical framework for the registration and analysis of multi-fascicle models for population studies of the brain microstructure. IEEE Trans Med Imaging. 2014 Feb; 33(2):504-17.
    View in: PubMed
    Score: 0.577
  4. Estimation of a multi-fascicle model from single B-value data with a population-informed prior. Med Image Comput Comput Assist Interv. 2013; 16(Pt 1):695-702.
    View in: PubMed
    Score: 0.544
  5. Registration and analysis of white matter group differences with a multi-fiber model. Med Image Comput Comput Assist Interv. 2012; 15(Pt 3):313-20.
    View in: PubMed
    Score: 0.508
  6. Spatially adaptive log-euclidean polyaffine registration based on sparse matches. Med Image Comput Comput Assist Interv. 2011; 14(Pt 2):590-7.
    View in: PubMed
    Score: 0.474
  7. A structural brain network of genetic vulnerability to psychiatric illness. Mol Psychiatry. 2021 Jun; 26(6):2089-2100.
    View in: PubMed
    Score: 0.226
  8. The Connectivity Fingerprint of the Fusiform Gyrus Captures the Risk of Developing Autism in Infants with Tuberous Sclerosis Complex. Cereb Cortex. 2020 04 14; 30(4):2199-2214.
    View in: PubMed
    Score: 0.225
  9. Extra-axonal restricted diffusion as an in-vivo marker of reactive microglia. Sci Rep. 2019 09 25; 9(1):13874.
    View in: PubMed
    Score: 0.217
  10. White matter mean diffusivity correlates with myelination in tuberous sclerosis complex. Ann Clin Transl Neurol. 2019 07; 6(7):1178-1190.
    View in: PubMed
    Score: 0.213
  11. Towards microstructure fingerprinting: Estimation of tissue properties from a dictionary of Monte Carlo diffusion MRI simulations. Neuroimage. 2019 01 01; 184:964-980.
    View in: PubMed
    Score: 0.203
  12. Assessing the validity of the approximation of diffusion-weighted-MRI signals from crossing fascicles by sums of signals from single fascicles. Magn Reson Med. 2018 04; 79(4):2332-2345.
    View in: PubMed
    Score: 0.186
  13. Characterizing brain tissue by assessment of the distribution of anisotropic microstructural environments in diffusion-compartment imaging (DIAMOND). Magn Reson Med. 2016 09; 76(3):963-77.
    View in: PubMed
    Score: 0.164
  14. Accelerated High Spatial Resolution Diffusion-Weighted Imaging. Inf Process Med Imaging. 2015; 24:69-81.
    View in: PubMed
    Score: 0.156
  15. Diffusion tensor imaging and related techniques in tuberous sclerosis complex: review and future directions. Future Neurol. 2013 Sep; 8(5):583-597.
    View in: PubMed
    Score: 0.143
  16. Brain functional networks in syndromic and non-syndromic autism: a graph theoretical study of EEG connectivity. BMC Med. 2013 Feb 27; 11:54.
    View in: PubMed
    Score: 0.138
  17. Characterizing the distribution of anisotropic micro-structural environments with diffusion-weighted imaging (DIAMOND). Med Image Comput Comput Assist Interv. 2013; 16(Pt 3):518-26.
    View in: PubMed
    Score: 0.136
  18. Reliable selection of the number of fascicles in diffusion images by estimation of the generalization error. Inf Process Med Imaging. 2013; 23:742-53.
    View in: PubMed
    Score: 0.136
  19. Block-Matching Distortion Correction of Echo-Planar Images With Opposite Phase Encoding Directions. IEEE Trans Med Imaging. 2017 05; 36(5):1106-1115.
    View in: PubMed
    Score: 0.045
  20. Tubers are neither static nor discrete: Evidence from serial diffusion tensor imaging. Neurology. 2015 Nov 03; 85(18):1536-45.
    View in: PubMed
    Score: 0.041
Connection Strength
The connection strength for co-authors is the sum of the scores for each of their shared publications.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.