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Conference papers
Spatially-variant morpho-Hessian filter: Efficient implementation and application
Abstract : Elongated objects are more difficult to filter than more isotropic ones because they locally comprise fewer pixels. For thin linear objects, this problem is compounded because there is only a restricted set of directions that can be used for filtering, and finding this local direction is not a simple problem. In addition, disconnections can easily appear due to noise. In this paper we tackle both issues by combining a linear filter for direction finding and a morphological one for filtering. More specifically, we use the eigen-analysis of the Hessian for detecting thin, linear objects, and a spatially-variant opening or closing for their enhancement and reconnection. We discuss the theory of spatially-variant morphological filters and present an efficient algorithm. The resulting spatially-variant morphological filter is shown to successfully enhance directions in 2D and 3D examples illustrated with a brain blood vessel segmentation problem.
Cited literature [30 references]
https://hal-upec-upem.archives-ouvertes.fr/hal-00622432
Contributor : Hugues Talbot Connect in order to contact the contributor
Submitted on : Wednesday, September 25, 2013 - 12:04:24 PM
Last modification on : Saturday, January 15, 2022 - 3:57:30 AM
Long-term archiving on: : Thursday, December 26, 2013 - 2:30:26 AM
Contributor : Hugues Talbot Connect in order to contact the contributor
Submitted on : Wednesday, September 25, 2013 - 12:04:24 PM
Last modification on : Saturday, January 15, 2022 - 3:57:30 AM
Long-term archiving on: : Thursday, December 26, 2013 - 2:30:26 AM
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