Please use this identifier to cite or link to this item:
Title: Evaluation of a semi-automatic segmentation algorithm in 3D intraoperative ultrasound brain angiography
Authors: Chalopin, Claire
Krissian, Karl
Meixensberger, Jurgen
Muns, Andrea
Arlt, Felix
Lindner, Dirk
UNESCO Clasification: 3314 Tecnología médica
Keywords: Blood Vessel
Issue Date: 2013
Journal: Biomedizinische Technik (Berlin. Zeitschrift) 
Abstract: In this work, we adapted a semi-automatic segmentation algorithm for vascular structures to extract cerebral blood vessels in the 3D intraoperative contrastenhanced ultrasound angiographic (3D-iUSA) data of the brain. We quantitatively evaluated the segmentation method with a physical vascular phantom. The geometrical features of the segmentation model generated by the algorithm were compared with the theoretical tube values and manual delineations provided by observers. For a silicon tube with a radius of 2 mm, the results showed that the algorithm overestimated the lumen radii values by about 1 mm, representing one voxel in the 3D-iUSA data. However, the observers were more hindered by noise and artifacts in the data, resulting in a larger overestimation of the tube lumen (twice the reference size). The first results on 3D-iUSA patient data showed that the algorithm could correctly restitute the main vascular segments with realistic geometrical features data, despite noise, artifacts and unclear blood vessel borders. A future aim of this work is to provide neurosurgeons with a visualization tool to navigate through the brain during aneurysm clipping operations.
ISSN: 0013-5585
DOI: 10.1515/bmt-2012-0089
Source: Biomedizinische Technik [ISSN 0013-5585], v. 58 (3), p. 293-302, (Junio 2013)
Appears in Collections:Artículos
Show full item record


checked on Sep 20, 2020

Page view(s)

checked on Sep 20, 2020

Google ScholarTM




Export metadata

Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.