Difference between revisions of "Projects:AffineSegmentSlicer2"
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This module can be used to perform semi-automatic segmentation by evolving an initial surface in 3D. The method uses a 3D | This module can be used to perform semi-automatic segmentation by evolving an initial surface in 3D. The method uses a 3D | ||
affine invariant edge detector to create potential well where the evolving surface converges. Use fiducials to create | affine invariant edge detector to create potential well where the evolving surface converges. Use fiducials to create | ||
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iterations untill it converges to the object boundary. To make the surface smooth, use the smooth button for a few iterations. | iterations untill it converges to the object boundary. To make the surface smooth, use the smooth button for a few iterations. | ||
Technical details about this method can be found in the paper mentioned here. | Technical details about this method can be found in the paper mentioned here. | ||
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* [Y. Rathi, P. Olver, G. Sapiro, and A. Tannenbaum. '''Affine''' Invariant Surface Evolutions for 3D Image Segmentation. In IS&T/SPIE Electronic Imaging, 2006] | * [Y. Rathi, P. Olver, G. Sapiro, and A. Tannenbaum. '''Affine''' Invariant Surface Evolutions for 3D Image Segmentation. In IS&T/SPIE Electronic Imaging, 2006] | ||
Revision as of 16:28, 2 April 2007
Home < Projects:AffineSegmentSlicer2Objective
This module can be used to perform semi-automatic segmentation by evolving an initial surface in 3D. The method uses a 3D affine invariant edge detector to create potential well where the evolving surface converges. Use fiducials to create initial contours (spheres) inside the object of interest. Use the expand button to inflate the initial contours for several iterations untill it converges to the object boundary. To make the surface smooth, use the smooth button for a few iterations. Technical details about this method can be found in the paper mentioned here.
Links
- [Y. Rathi, P. Olver, G. Sapiro, and A. Tannenbaum. Affine Invariant Surface Evolutions for 3D Image Segmentation. In IS&T/SPIE Electronic Imaging, 2006]
