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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Moussa, Richard Beurton-Aimar, Marie Desbarats, Pascal |
| Copyright Year | 2011 |
| Description | Author affiliation: LaBRI, University of Bordeaux, 351, cours de la Libration F-33405 Talence cedex, France (Moussa, Richard; Beurton-Aimar, Marie; Desbarats, Pascal) |
| Abstract | Image segmentation is a crucial operation for image processing. It is always the starting point for analysis processes, including registration, shape analysis, motion detection, visualization, quantitative estimations of linear distances, areas, volumes. For these purposes, segmentation consists in categorizing voxels into classes based on their local intensity, spatial location, neighborhood or shape characteristics. The difficulty of the segmentation methods results stability comes from the different types of noise in medical images. These noises need to be taken into account for all image segmentation methods. In this paper, we present two Multi-Agent models based on social ants. The first system is a classical one using voxel gradient to set agents movements and the second is an original one using intervoxel informations to set agents movements between the voxels. The simulation results on brain $MR^{1}$ images show that the method based on intervoxel shiftings appears to be more robust to noise than the classical one based on voxel gradient and the Sobel operator. Finally, we will discuss how these first results could be improved by adding additional characteristics to the ants and their environment. |
| Starting Page | 1 |
| Ending Page | 8 |
| File Size | 642444 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424478347 |
| e-ISBN | 9781424478354 |
| DOI | 10.1109/CEC.2011.5950006 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-06-05 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image segmentation Noise Mathematical model Image edge detection Three dimensional displays Equations Gray-scale Medical imaging Social ants Multi-Agent system Evolutionary computing |
| Content Type | Text |
| Resource Type | Article |
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