✦ LIBER ✦

Application of diffusion tensor MRI to neurological segmentation

✍ Scribed by Andrew Simmons; Derek K. Jones; Mark A. Horsfield; Steven C. R. Williams

Publisher: John Wiley and Sons
Year: 1999
Tongue: English
Weight: 553 KB
Volume: 10
Category: Article
ISSN: 0899-9457
DOI: 10.1002/(sici)1098-1098(1999)10:3<273::aid-ima8>3.0.co;2-e

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✦ Synopsis

We consider the application of segmentation based on cluster classification techniques to a series of images derived from the diffusion tensor. The extension of a sophisticated cluster simulation tool used for optimizing data acquisition for such segmentation methods to diffusion-based images is described. The characteristics of a variety of diffusion-based images including fractional anisotropy images, diffusion tensor trace images, and isotropically diffusionweighted images are considered and their application to neurological image segmentation is investigated. The critical effect of the signalto-noise ratio on fractional anisotropy is analyzed and limitations of current echo planar-based strategies are discussed. Segmentation is shown to be possible using only images derived from the diffusion tensor, and such images are shown to offer exciting new avenues for neurological segmentation.

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