A Robust Algorithm for Fiber-Bundle Atlas Construction

In this paper, we demonstrate an integrated registration and clustering algorithm to compute an atlas of fiber- bundles from a set of multi-subject diffusion weighted MR images. We formulate a maximum likelihood problem which the proposed method solves using a generalized Expectation Maximization (E...

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Bibliographic Details
Published in2007 IEEE 11th International Conference on Computer Vision pp. 1 - 8
Main Authors Ziyan, U., Sabuncu, M.R., Eric, W., Grimson, L., Westin, C.-F.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2007
Subjects
Anatomical structure
Clustering algorithms
Computer science
Diffusion tensor imaging
Iterative algorithms
Nerve fibers
Noise reduction
Pathology
Robustness
Tensile stress
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Summary:In this paper, we demonstrate an integrated registration and clustering algorithm to compute an atlas of fiber- bundles from a set of multi-subject diffusion weighted MR images. We formulate a maximum likelihood problem which the proposed method solves using a generalized Expectation Maximization (EM) framework. Additionally, the algorithm employs an outlier rejection and denoising strategy to produce sharp probabilistic maps of certain bundles of interest. This map is potentially useful for making diffusion measurements in a common coordinate system to identify pathology related changes or developmental trends.
ISBN:1424416302
9781424416301
ISSN:1550-5499
DOI:10.1109/ICCV.2007.4409143