@inproceedings{f14a10cbf9ae4201bf0a105aea76192b,
title = "AKI tabanli ikinci mertebeli tens{\"o}r modeli kullanan beyin kan damarlari b{\"o}l{\"u}tleme y{\"o}ntemi",
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.",
keywords = "brain vessels, Digital Subtraction Angiography (DSA), flux, Rotational Angiography (RA), segmentation, tractography, tubular structures, vessel trees",
author = "Suheyla Cetin and Gozde Unal",
year = "2014",
doi = "10.1109/SIU.2014.6830437",
language = "T{\"u}rk{\c c}e",
isbn = "9781479948741",
series = "2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings",
publisher = "IEEE Computer Society",
pages = "1146--1149",
booktitle = "2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings",
address = "United States",
note = "2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 ; Conference date: 23-04-2014 Through 25-04-2014",
}