 |
Conference papers
A non-local fuzzy segmentation method: Application to brain MRI
Abstract : The Fuzzy C-Means algorithm is a widely used and flexible approach for brain tissue segmentation from 3D MRI. Despite its recent enrichment by addition of a spatial dependency to its formulation, it remains quite sensitive to noise. In order to improve its reliability in noisy contexts, we propose a way to select the most suitable example regions for regularisation. This approach inspired by the Non-Local Mean strategy used in image restoration is based on the computation of weights modelling the grey-level similarity between the neighbourhoods being compared. Experiments were performed on MRI data and results illustrate the usefulness of the approach in the context of brain tissue classification.
Cited literature [12 references]
https://hal.univ-reims.fr/hal-01695014
Contributor : Nicolas Passat <>
Submitted on : Saturday, March 3, 2018 - 4:54:15 PM
Last modification on : Wednesday, August 7, 2019 - 12:16:02 PM
Long-term archiving on: : Monday, June 4, 2018 - 3:57:02 PM
Contributor : Nicolas Passat <>
Submitted on : Saturday, March 3, 2018 - 4:54:15 PM
Last modification on : Wednesday, August 7, 2019 - 12:16:02 PM
Long-term archiving on: : Monday, June 4, 2018 - 3:57:02 PM
File
Caldairou CAIP 2009.pdf
Files produced by the author(s)