Denoising of brain DW-MR data by single and multiple diffusion kernels
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| Format: | Artículo científico |
| Language: | en |
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Universidad de Guanajuato
2010
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| author | Alonso Ramírez-Manzanares |
| author_facet | Alonso Ramírez-Manzanares |
| contents | Denoising of brain DW-MR data by single and multiple diffusion kernels Alonso Ramírez-Manzanares Jonathan Rafael Patiño Manzar Ashtari Multidisciplinarias (Ciencias Sociales) MRI DWI Multi tensor Filtrado de ruido Diffusion Weighted Magnetic Resonance Imaging is widely used to study the structure of the fiber pathways of white matter in the brain. However, the recovered axon orientations can be prone to error because of the low signal to noise ratio. Spatial regularization can reduce the error, but it must be done carefully so that real spatial information is not removed and false orientations are not introduced. In this paper we investigate the advantages of applying an anisotropic filter based on single and multiple axon bundle orientation kernels. To this end, we compute local diffusion kernels based on Diffusion Tensor and multi Diffusion Tensor models. We show the benefits of our approach to three different types of DW-MRI data: synthetic, in vivo human, and acquired from a diffusion phantom. 2010 artículo científico 0188-6266 https://www.redalyc.org/articulo.oa?id=41615947006 en http://www.redalyc.org/revista.oa?id=416 Acta Universitaria application/pdf Universidad de Guanajuato Acta Universitaria (México) Num.3 Vol.20 |
| format | Artículo científico |
| id | redalyc_41615947006 |
| institution | Redalyc |
| language | en |
| publishDate | 2010 |
| publisher | Universidad de Guanajuato |
| spellingShingle | Denoising of brain DW-MR data by single and multiple diffusion kernels Alonso Ramírez-Manzanares Multidisciplinarias (Ciencias Sociales) MRI DWI Multi tensor Filtrado de ruido Denoising of brain DW-MR data by single and multiple diffusion kernels Alonso Ramírez-Manzanares Jonathan Rafael Patiño Manzar Ashtari Multidisciplinarias (Ciencias Sociales) MRI DWI Multi tensor Filtrado de ruido Diffusion Weighted Magnetic Resonance Imaging is widely used to study the structure of the fiber pathways of white matter in the brain. However, the recovered axon orientations can be prone to error because of the low signal to noise ratio. Spatial regularization can reduce the error, but it must be done carefully so that real spatial information is not removed and false orientations are not introduced. In this paper we investigate the advantages of applying an anisotropic filter based on single and multiple axon bundle orientation kernels. To this end, we compute local diffusion kernels based on Diffusion Tensor and multi Diffusion Tensor models. We show the benefits of our approach to three different types of DW-MRI data: synthetic, in vivo human, and acquired from a diffusion phantom. 2010 artículo científico 0188-6266 https://www.redalyc.org/articulo.oa?id=41615947006 en http://www.redalyc.org/revista.oa?id=416 Acta Universitaria application/pdf Universidad de Guanajuato Acta Universitaria (México) Num.3 Vol.20 |
| title | Denoising of brain DW-MR data by single and multiple diffusion kernels |
| topic | Multidisciplinarias (Ciencias Sociales) MRI DWI Multi tensor Filtrado de ruido |
| url | https://www.redalyc.org/articulo.oa?id=41615947006 |