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(Page créée avec « jeudi 21 décembre 2017, 14h00 ===== 3D Medical Image Registration using Spectral Graph Features ===== Conférenciers : '''Ç. Bilen''' In this presentation, we study t... ») |
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===== 3D Medical Image Registration using Spectral Graph Features ===== | ===== 3D Medical Image Registration using Spectral Graph Features ===== | ||
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In this presentation, we study the spectral features on a 3D image to improve the medical image registration. The spectral features are basis vectors of a laplacian of a graph, and for medical images we generate graphs based on connectivity of tissues. The resulting approach is challenging to use on large 3-dimensional data, but these challenges are overcome by efficient representation of supervoxels instead of direct voxels. | In this presentation, we study the spectral features on a 3D image to improve the medical image registration. The spectral features are basis vectors of a laplacian of a graph, and for medical images we generate graphs based on connectivity of tissues. The resulting approach is challenging to use on large 3-dimensional data, but these challenges are overcome by efficient representation of supervoxels instead of direct voxels. | ||
Version actuelle datée du 23 janvier 2018 à 00:58
jeudi 21 décembre 2017, 14h00
3D Medical Image Registration using Spectral Graph Features
Conférenciers : Çağdaş Bilen
In this presentation, we study the spectral features on a 3D image to improve the medical image registration. The spectral features are basis vectors of a laplacian of a graph, and for medical images we generate graphs based on connectivity of tissues. The resulting approach is challenging to use on large 3-dimensional data, but these challenges are overcome by efficient representation of supervoxels instead of direct voxels.