Progressive and Efficient Multi-Resolution Representations for Brain Tractograms

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dc.contributor.authorMercier, Corentinen_US
dc.contributor.authorGori, Pietroen_US
dc.contributor.authorRohmer, Damienen_US
dc.contributor.authorCani, Marie-Pauleen_US
dc.contributor.authorBoubekeur, Tamyen_US
dc.contributor.authorThiery, Jean-Marcen_US
dc.contributor.authorBloch, Isabelleen_US
dc.contributor.editorPuig Puig, Anna and Schultz, Thomas and Vilanova, Anna and Hotz, Ingrid and Kozlikova, Barbora and Vázquez, Pere-Pauen_US
dc.date.accessioned2018-09-19T15:19:28Z
dc.date.available2018-09-19T15:19:28Z
dc.date.issued2018
dc.description.abstractCurrent tractography methods generate tractograms composed of millions of 3D polylines, called fibers, making visualization and interpretation extremely challenging, thus complexifying the use of this technique in a clinical environment. We propose to progressively simplify tractograms by grouping similar fibers into generalized cylinders. This produces a fine-grained multiresolution model that provides a progressive and real-time navigation through different levels of detail. This model preserves the overall structure of the tractogram and can be adapted to different measures of similarity. We also provide an efficient implementation of the method based on a Delaunay tetrahedralization. We illustrate our method using the Human Connectome Project dataset.en_US
dc.description.sectionheadersHead and Brain
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicine
dc.identifier.doi10.2312/vcbm.20181232
dc.identifier.isbn978-3-03868-056-7
dc.identifier.issn2070-5786
dc.identifier.pages89-93
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vcbm20181232
dc.identifier.urihttps://doi.org/10.2312/vcbm.20181232
dc.publisherThe Eurographics Associationen_US
dc.titleProgressive and Efficient Multi-Resolution Representations for Brain Tractogramsen_US
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VCBM 18: Eurographics Workshop on Visual Computing for Biology and Medicine