Ola Friman

Summary

Affiliation: Harvard University
Country: USA

Publications

  1. ncbi request reprint A Bayesian approach for stochastic white matter tractography
    Ola Friman
    Laboratory of Mathematics in Imaging, Department of Radiology, Brigham and Women s Hospital, Harvard Medical School, Boston, MA 02115, USA
    IEEE Trans Med Imaging 25:965-78. 2006
  2. ncbi request reprint Detection and detrending in fMRI data analysis
    Ola Friman
    Department of Radiology, Brigham and Women s Hospital, Harvard Medical School, Boston, MA, USA
    Neuroimage 22:645-55. 2004
  3. ncbi request reprint Resampling fMRI time series
    Ola Friman
    Department of Radiology, Brigham and Women s Hospital, Harvard Medical School, Thorn 323, 75 Francis Street, Boston, MA 02115, USA
    Neuroimage 25:859-67. 2005
  4. ncbi request reprint Uncertainty in white matter fiber tractography
    Ola Friman
    Laboratory of Mathematics in Imaging, Department of Radiology Brigham and Women s Hospital, Harvard Medical School, USA
    Med Image Comput Comput Assist Interv 8:107-14. 2005
  5. pmc Geometrically constrained two-tensor model for crossing tracts in DWI
    Sharon Peled
    Harvard Center for Neurodegeneration and Repair, Boston, MA 02115, USA
    Magn Reson Imaging 24:1263-70. 2006
  6. ncbi request reprint Multiple channel detection of steady-state visual evoked potentials for brain-computer interfaces
    Ola Friman
    Institute of Automation, University of Bremen, Otto Hahn Allee 1, 28359 Bremen, Germany
    IEEE Trans Biomed Eng 54:742-50. 2007
  7. ncbi request reprint Adaptive analysis of fMRI data
    Ola Friman
    Department of Biomedical Engineering, Linkoping University, Linkoping, Sweden
    Neuroimage 19:837-45. 2003
  8. ncbi request reprint Exploratory fMRI analysis by autocorrelation maximization
    Ola Friman
    Department of Biomedical Engineering, Linkoping University, University Hospital, Linkoping, Sweden
    Neuroimage 16:454-64. 2002
  9. pmc CellProfiler: image analysis software for identifying and quantifying cell phenotypes
    Anne E Carpenter
    Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
    Genome Biol 7:R100. 2006
  10. ncbi request reprint Detection of neural activity in fMRI using maximum correlation modeling
    Ola Friman
    Department of Biomedical Engineering, Linkoping University, Linkoping, Sweden
    Neuroimage 15:386-95. 2002

Collaborators

Detail Information

Publications10

  1. ncbi request reprint A Bayesian approach for stochastic white matter tractography
    Ola Friman
    Laboratory of Mathematics in Imaging, Department of Radiology, Brigham and Women s Hospital, Harvard Medical School, Boston, MA 02115, USA
    IEEE Trans Med Imaging 25:965-78. 2006
    ..Theory for estimating global connectivity is also presented, as well as a theorem that facilitates the estimation of the parameters in a constrained tensor model of the local water diffusion profile...
  2. ncbi request reprint Detection and detrending in fMRI data analysis
    Ola Friman
    Department of Radiology, Brigham and Women s Hospital, Harvard Medical School, Boston, MA, USA
    Neuroimage 22:645-55. 2004
    ..The value of such a model lies in its ability to remove drift components that otherwise would have contributed to a colored noise structure in the voxel time series...
  3. ncbi request reprint Resampling fMRI time series
    Ola Friman
    Department of Radiology, Brigham and Women s Hospital, Harvard Medical School, Thorn 323, 75 Francis Street, Boston, MA 02115, USA
    Neuroimage 25:859-67. 2005
    ..While blocked designs can induce large biases, event-related designs generate significantly smaller biases. Results supporting these claims are provided...
  4. ncbi request reprint Uncertainty in white matter fiber tractography
    Ola Friman
    Laboratory of Mathematics in Imaging, Department of Radiology Brigham and Women s Hospital, Harvard Medical School, USA
    Med Image Comput Comput Assist Interv 8:107-14. 2005
    ..We also provide a theorem that facilitates the estimation of the parameters in this diffusion model, making the presented method simple to implement...
  5. pmc Geometrically constrained two-tensor model for crossing tracts in DWI
    Sharon Peled
    Harvard Center for Neurodegeneration and Repair, Boston, MA 02115, USA
    Magn Reson Imaging 24:1263-70. 2006
    ..Upon evaluation in simulations and application to in vivo human brain DTI data, the method appears to be robust and practical and, if correctly applied, could elucidate tract directions at critical points of uncertainty...
  6. ncbi request reprint Multiple channel detection of steady-state visual evoked potentials for brain-computer interfaces
    Ola Friman
    Institute of Automation, University of Bremen, Otto Hahn Allee 1, 28359 Bremen, Germany
    IEEE Trans Biomed Eng 54:742-50. 2007
    ..An additional advantage of the presented methodology is that it is fully online, i.e., no calibration data for noise estimation, feature extraction, or electrode selection is needed...
  7. ncbi request reprint Adaptive analysis of fMRI data
    Ola Friman
    Department of Biomedical Engineering, Linkoping University, Linkoping, Sweden
    Neuroimage 19:837-45. 2003
    ..Results that demonstrate how each of these parts significantly improves the detection of brain activity, with a computation time well within limits for practical use, are provided...
  8. ncbi request reprint Exploratory fMRI analysis by autocorrelation maximization
    Ola Friman
    Department of Biomedical Engineering, Linkoping University, University Hospital, Linkoping, Sweden
    Neuroimage 16:454-64. 2002
    ..The relation to Principal Component Analysis and Independent Component Analysis is discussed and the performance of the methods is compared using both simulated and real data...
  9. pmc CellProfiler: image analysis software for identifying and quantifying cell phenotypes
    Anne E Carpenter
    Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
    Genome Biol 7:R100. 2006
    ....
  10. ncbi request reprint Detection of neural activity in fMRI using maximum correlation modeling
    Ola Friman
    Department of Biomedical Engineering, Linkoping University, Linkoping, Sweden
    Neuroimage 15:386-95. 2002
    ..Comparisons to traditional analysis methods are made using both synthetic and real data. The results indicate that the maximum correlation modeling approach is a strong alternative for analyzing fMRI data...