Cortex Segmentation: a Fast Variational Geometric Approach
.
Cortex Segmentation: A Fast Variational Geometric Approach.
In LevelSet01, 2001
Online Version
A pdf version is available for download.
Abstract
An automatic cortical gray matter segmentation from a three-dimensional brain images (MR or CT) is a well known problem in medical image processing. In this paper we formulate it as geometric variational problem for propagation of two coupled bounding surfaces. An efficient numerical scheme is used to implement the geodesic active surface model. Experimental results of cortex segmentation on real three-dimensional MR data are provided.
Co-authors
Bibtex Entry
@inproceedings{GoldenbergKRR01i,
title = {Cortex Segmentation: A Fast Variational Geometric Approach},
author = {Roman Goldenberg and Ron Kimmel and Ehud Rivlin and Michael Rudzsky},
year = {2001},
booktitle = {LevelSet01},
abstract = {An automatic cortical gray matter segmentation from a three-dimensional brain images (MR or CT) is a well known problem in medical image processing. In this paper we formulate it as geometric variational problem for propagation of two coupled bounding surfaces. An efficient numerical scheme is used to implement the geodesic active surface model. Experimental results of cortex segmentation on real three-dimensional MR data are provided.}
}