Name
Abstract | ||
|---|---|---|
The corpus callosum (CC) is one of the most important white matter structures of the brain, interconnecting the two cerebral hemispheres, and is related to several neurodegenerative diseases. Since segmentation is usually the first step for studies in this structure, and manual volumetric segmentation is a very time-consuming task, it is important to have a robust automatic method for CC segmentation. We propose here an approach for fully automatic 3D segmentation of the CC in the magnetic resonance diffusion tensor images. The method uses the watershed transform and is performed on the fractional anisotropy (FA) map weighted by the projection of the principal eigenvector in the left-right direction. The section of the CC in the midsagittal slice is used as seed for the volumetric segmentation. Experiments with real diffusion MRI data showed that the proposed method is able to quickly segment the CC without any user intervention, with great results when compared to manual segmentation. Since it is simple, fast and does not require parameter settings, the proposed method is well suited for clinical applications. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1117/12.911619 | Proceedings of SPIE |
Keywords | Field | DocType |
corpus callosum,fractional anisotropy,diffusion tensor image,magnetic resonance,segmentation,watershed transform | Computer vision,Diffusion MRI,White matter,Fractional anisotropy,Segmentation,Watershed,Artificial intelligence,Corpus callosum,Physics,Magnetic resonance imaging | Conference |
Volume | ISSN | Citations |
8314 | 0277-786X | 1 |
PageRank | References | Authors |
0.35 | 8 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pedro Freitas | 1 | 3 | 0.73 |
| Leticia Rittner | 2 | 82 | 12.95 |
| Simone Appenzeller | 3 | 14 | 4.99 |
| a t lapa | 4 | 1 | 0.69 |
| Roberto de Alencar Lotufo | 5 | 572 | 53.61 |