Magnetic resonance image tissue classification using a partial volume model.

  title={Magnetic resonance image tissue classification using a partial volume model.},
  author={David W. Shattuck and S. R. Sandor-Leahy and K A Schaper and David A. Rottenberg and Richard M. Leahy},
  volume={13 5},
We describe a sequence of low-level operations to isolate and classify brain tissue within T1-weighted magnetic resonance images (MRI). Our method first removes nonbrain tissue using a combination of anisotropic diffusion filtering, edge detection, and mathematical morphology. We compensate for image nonuniformities due to magnetic field inhomogeneities by fitting a tricubic B-spline gain field to local estimates of the image nonuniformity spaced throughout the MRI volume. The local estimates… CONTINUE READING
Highly Influential
This paper has highly influenced 100 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS


Publications citing this paper.
Showing 1-10 of 460 extracted citations


Publications referenced by this paper.
Showing 1-10 of 60 references

Brainstorm: A Matlab toolbox for the processing of MEG and EEG signals

  • S. Baillet, J. Mosher, R. Leahy, D. Shattuck
  • NeuroImage 9:S246.
  • 1999
Highly Influential
6 Excerpts

Intracranial Boundary Detection and Radio Frequency Correction in Magnetic Resonance Images

  • B. Mackiewich
  • Simon Fraser Univ., Burnaby, British Columbia…
  • 1995
Highly Influential
4 Excerpts

Similar Papers

Loading similar papers…