Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/74040
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
Neurosurgery
Phantom
Visualization
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.
URI: http://hdl.handle.net/10553/74040
ISSN: 0013-5585
DOI: 10.1515/bmt-2012-0089
Source: Biomedizinische Technik [ISSN 0013-5585], v. 58 (3), p. 293-302, (Junio 2013)
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