Cortex Segmentation - A Fast Variational Geometric Approach

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An automatic cortical gray matter segmentation from a three-dimensional (3-D) brain images [magnetic resonance (MR) or computed tomography] is a well known problem in medical image processing. In this paper, we first formulate it as a geometric variational problem for propagation of two coupled bounding surfaces. An efficient numerical scheme is then used to implement the geodesic active surface model. Experimental results of cortex segmentation on real 3-D MR data are provided.

Roman Goldenberg, Ron Kimmel, Ehud Rivlin, Michael

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Geometric Variational Problem | Gray Matter Segmentation | Real 3-d Mr | TMI 2002 |

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Added	23 Dec 2010
Updated	23 Dec 2010
Type	Journal
Year	2002
Where	TMI
Authors	Roman Goldenberg, Ron Kimmel, Ehud Rivlin, Michael Rudzsky

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Cortex Segmentation - A Fast Variational Geometric Approach

Geometric Variational Problem | Gray Matter Segmentation | Real 3-d Mr | TMI 2002 |

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