A cerebral blood vessels segmentation method using a flux based second order tensor model

Warning The system is temporarily closed to updates for reporting purpose.

Çetin, Süheyla and Ünal, Gözde (2014) A cerebral blood vessels segmentation method using a flux based second order tensor model. In: 22nd Signal Processing and Communications Applications Conference (SIU 2014), Trabzon, Turkiye

Full text not available from this repository. (Request a copy)

Abstract

In this paper, we view the segmentation of cerebral blood vessels from Digital Subtraction Angiography (DSA) and Rotational Angiography (RA) problem from a tensor estimation and tractography perspective as in diffusion tensor imaging (DTI). We have developed a flux based multi-directional cylinder model that fits to a second-order tensor whose principal eigenvector represents the vessel's centerline. This anisotropic tensor inside the vessel drives the segmentation analogously to a tractography approach in DTI analysis starting from a seed point used as initialization.
Item Type: Papers in Conference Proceedings
Subjects: Q Science > QA Mathematics > QA075 Electronic computers. Computer science
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Electronics
Faculty of Engineering and Natural Sciences
Depositing User: Gözde Ünal
Date Deposited: 14 Dec 2014 21:29
Last Modified: 26 Apr 2022 09:17
URI: https://research.sabanciuniv.edu/id/eprint/25863

Actions (login required)

View Item
View Item