Cerebral vein analysis provides a fundamental tool to study brain diseases such as neurodegenerative disorders or traumatic brain injuries. In order to assess the vascular anatomy, manual segmentation approaches can be used but are observer-dependent and time-consuming. In the present work, a fully automated cerebral vein segmentation method is proposed, based on a multiscale and multiparametric approach. The combined investigation of the R‡2- and a Vesselness probabilitymap was used to obtain a fast and highly reliable classification of venous voxels. A semiquantitative analysis showed that our approach outperformed the previous state-of-the-art algorithm both in sensitivity and specificity. Inclusion of this tool within a parametric brain framework may therefore pave the way for a quantitative study of the intracranial venous system.

A multiparametric and multiscale approach to automated segmentation of brain veins / Monti, S; Palma, G; Borrelli, P; Tedeschi, Enrico; Cocozza, Sirio; Salvatore, Marco; Mancini, Marcello. - 2015-:(2015), pp. 3041-3044. (Intervento presentato al convegno 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 tenutosi a MiCo Center, Milano Congressi Center, ita nel 2015) [10.1109/EMBC.2015.7319033].

A multiparametric and multiscale approach to automated segmentation of brain veins

TEDESCHI, ENRICO;COCOZZA, SIRIO;SALVATORE, MARCO;MANCINI, Marcello
2015

Abstract

Cerebral vein analysis provides a fundamental tool to study brain diseases such as neurodegenerative disorders or traumatic brain injuries. In order to assess the vascular anatomy, manual segmentation approaches can be used but are observer-dependent and time-consuming. In the present work, a fully automated cerebral vein segmentation method is proposed, based on a multiscale and multiparametric approach. The combined investigation of the R‡2- and a Vesselness probabilitymap was used to obtain a fast and highly reliable classification of venous voxels. A semiquantitative analysis showed that our approach outperformed the previous state-of-the-art algorithm both in sensitivity and specificity. Inclusion of this tool within a parametric brain framework may therefore pave the way for a quantitative study of the intracranial venous system.
2015
9781424492718
9781424492718
A multiparametric and multiscale approach to automated segmentation of brain veins / Monti, S; Palma, G; Borrelli, P; Tedeschi, Enrico; Cocozza, Sirio; Salvatore, Marco; Mancini, Marcello. - 2015-:(2015), pp. 3041-3044. (Intervento presentato al convegno 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 tenutosi a MiCo Center, Milano Congressi Center, ita nel 2015) [10.1109/EMBC.2015.7319033].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/658039
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