Three-dimensional segmentation and interpolation of magnetic resonance brain images

M Joliot, BM Mazoyer - IEEE Transactions on Medical Imaging, 1993 - ieeexplore.ieee.org
IEEE Transactions on Medical Imaging, 1993ieeexplore.ieee.org
The authors propose a method for the 3-D reconstruction of the brain from anisotropic
magnetic resonance imaging (MRI) brain data. The method essentially consists in two
original algorithms both for segmentation and for interpolation of the MRI data. The
segmentation process is performed in three steps. A gray level thresholding of the white and
gray matter tissue is performed on the brain MR raw data. A global white matter
segmentation is automatically performed with a global 3-D connectivity algorithm which …
The authors propose a method for the 3-D reconstruction of the brain from anisotropic magnetic resonance imaging (MRI) brain data. The method essentially consists in two original algorithms both for segmentation and for interpolation of the MRI data. The segmentation process is performed in three steps. A gray level thresholding of the white and gray matter tissue is performed on the brain MR raw data. A global white matter segmentation is automatically performed with a global 3-D connectivity algorithm which takes into account the anisotropy of the MRI voxel. The gray matter is segmented with a local 3-D connectivity algorithm. Mathematical morphology tools are used to interpolate slices. The whole process gives an isotropic binary representation of both gray and white matter which are available for 3-D surface rendering. The power and practicality of this method have been tested on four brain datasets. The segmentation algorithm favorably compares to a manual one. The interpolation algorithm was compared to the shaped-based method both quantitatively and qualitatively.< >
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