Rician noise removal in diffusion tensor MRI.

Rician noise removal in diffusion tensor MRI. Research Abstract Details 

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Rician noise removal in diffusion tensor MRI. Abstract Text:

Saurav Basu,Thomas Fletcher,Ross Whitaker,

Rician noise introduces a bias into MRI measurements that can have a significant impact on the shapes and orientations of tensors in diffusion tensor magnetic resonance images. This is less of a problem in structural MRI, because this bias is signal dependent and it does not seriously impair tissue identification or clinical diagnoses. However, diffusion imaging is used extensively for quantitative evaluations, and the tensors used in those evaluations are biased in ways that depend on orientation and signal levels. This paper presents a strategy for filtering diffusion tensor magnetic resonance images that addresses these issues. The method is a maximum a posteriori estimation technique that operates directly on the diffusion weighted images and accounts for the biases introduced by Rician noise. We account for Rician noise through a data likelihood term that is combined with a spatial smoothing prior. The method compares favorably with several other approaches from the literature, including methods that filter diffusion weighted imagery and those that operate directly on the diffusion tensors.

Rician noise removal in diffusion tensor MRI. Publishing Authors By Initials

S Basu,T Fletcher,R Whitaker,

For similar investigative techniques: epidemiologic methods: statistics as topic: sensitivity and specificity research abstracts see: investigative techniques: epidemiologic methods: statistics as topic: sensitivity and specificity research

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Rician noise removal in diffusion tensor MRI. Journal Published:

PUBLICATION TYPE: Research Support, N.I.H., Extr

Journal: Medical image computing and computer-assisted inte

VOLUME: 9

Page Numbers: 117-25

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DAY: 3

MONTH: 12

YEAR: 2006

Rician noise removal in diffusion tensor MRI. Information

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LANGUAGE: eng

NlmUniqueID: 101249582

Rician noise removal in diffusion tensor MRI. Keywords Mesh Terms:

KEYWORDS: Sensitivity and Specificity

MESH TERMS: methods

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Grant and Affiliation Information for Rician noise removal in diffusion tensor MRI.

AFFILIATION: University of Utah, School of Computing, Salt Lake City, UT 84112, USA.

Country: Germany

AGENCY: United States NIBIB

GRANT: U54 EB005149

ACRONYM: EB

MEDLINETA: Med Image Comput Comput Assist

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