title: Evaluation of a semi-automatic segmentation algorithm in 3D intraoperative ultrasound brain angiography.
abstract: In this work, we adapted a semi-automatic segmentation algorithm for vascular structures to extract cerebral blood vessels in the 3D intraoperative contrast-enhanced 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.
authors: Innovation Center Computer Assisted Surgery, University of Leipzig, Leipzig, Germany. claire.chalopin@iccas.de
authors: Claire
authors: C
authors: Chalopin
authors: Karl
authors: K
authors: Krissian
authors: Jürgen
authors: J
authors: Meixensberger
authors: Andrea
authors: A
authors: Müns
authors: Felix
authors: F
authors: Arlt
authors: Dirk
authors: D
authors: Lindner
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001783:Blood Flow Velocity / Q000502:physiology; D002536:Cerebral Arteries / Q000000981:diagnostic imaging / Q000502:physiology*; D002560:Cerebrovascular Circulation / Q000502:physiology*; D004453:Echoencephalography / Q000295:instrumentation / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016343:Monitoring, Intraoperative / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D025321:Surgery, Computer-Assisted / Q000379:methods*