Diffusion-weighted imaging: Difference between revisions
m Bringing "External links" and "See also" sections in line with Manual of Style recommendations. |
mNo edit summary |
||
| Line 1: | Line 1: | ||
Diffusion-weighted imaging is a specific [[MRI]] modality that produces in vivo magnetic resonances images of biological tissues weighted with the local characteristics of water diffusion. |
'''Diffusion-weighted imaging''' is a specific [[MRI]] modality that produces in vivo magnetic resonances images of biological tissues weighted with the local characteristics of water diffusion. |
||
More precisely, given a spacial direction and a chosen amount of time during which water molecules are left free to diffuse, a sophisticated MRI scanner produces a T2 (3D) image attenuated according to the intensity of the diffusion. The more attenuated the image is at a given position, the more [[diffusion]] there is locally. Interestingly, this image intensity varies whenever the spatial direction or the diffusion gradient is changed. As a consequence, simple models have been proposed to account for such changes, such as the diffusion tensor model. |
More precisely, given a spacial direction and a chosen amount of time during which water molecules are left free to diffuse, a sophisticated MRI scanner produces a T2 (3D) image attenuated according to the intensity of the diffusion. The more attenuated the image is at a given position, the more [[diffusion]] there is locally. Interestingly, this image intensity varies whenever the spatial direction or the diffusion gradient is changed. As a consequence, simple models have been proposed to account for such changes, such as the diffusion tensor model. |
||
Revision as of 10:54, 12 January 2006
Diffusion-weighted imaging is a specific MRI modality that produces in vivo magnetic resonances images of biological tissues weighted with the local characteristics of water diffusion.
More precisely, given a spacial direction and a chosen amount of time during which water molecules are left free to diffuse, a sophisticated MRI scanner produces a T2 (3D) image attenuated according to the intensity of the diffusion. The more attenuated the image is at a given position, the more diffusion there is locally. Interestingly, this image intensity varies whenever the spatial direction or the diffusion gradient is changed. As a consequence, simple models have been proposed to account for such changes, such as the diffusion tensor model.
Diffusion-weighted images are very useful to diagnose vascular strokes in the brain, to study the diseases of the white matter or to (try to) infer the connectivity of the brain (i.e. tractography; try to see which part of the cortex is connected to another one, and so on).