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A Novel White Matter Fibre Tracking Algorithm using Probabilistic Tractography and Average Curves

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dc.contributor.author Nagulan, R.
dc.contributor.author Andrew, S.
dc.contributor.author Oleg, D.
dc.contributor.author Ali, H.
dc.date.accessioned 2019-10-24T05:30:06Z
dc.date.accessioned 2022-06-27T04:11:23Z
dc.date.available 2019-10-24T05:30:06Z
dc.date.available 2022-06-27T04:11:23Z
dc.date.issued 2010
dc.identifier.uri http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/1270
dc.description.abstract This paper presents a novel white matter fibretractography approach using average curves of probabilistic fibre tracking measures. We compute”representative” curves from the original probabilistic curve-set using two different averaging methods. These typical curves overcome a number of the limitations of deterministic and probabilistic approaches. They produce strong connections to every anatomically distinct fibre tract from a seed point and also convey important information about the underlying probability distribution. A new clustering algorithm is employed to separate fibres into branches before applying averaging methods. The performance of the technique is verified on a wide range of seed points using a phantom dataset and an in vivo dataset. en_US
dc.language.iso en_US en_US
dc.publisher Springer Berlin/Heidelberg MICCAI en_US
dc.subject Probabilistic fiber tracking; diffusion tensor imaging en_US
dc.subject average curves en_US
dc.subject average curves en_US
dc.title A Novel White Matter Fibre Tracking Algorithm using Probabilistic Tractography and Average Curves en_US
dc.type Article en_US


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