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 |