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Skeletonization method for vessel delineation of arteriovenous malformation

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Abstract
Cerebral arteriovenous malformation (AVM) presents a great health threat due to its high probability of rupture that can cause severe brain damage. Image segmentation alone is not sufficient to support AVM embolization procedure. In order to successfully navigate the catheter and perform embolization, the segmented blood vessels need to be classified into feeding arteries, draining veins and the AVM nidus. For this reason we address here the AVM localization and vessel decomposition problem. We propose in this paper a novel AVM localization and vessel delineation method using ordered thinning-based skeletonization. The main focus of vessel delineation is the delineation of draining veins since it is essential for the embolization procedure. The main contribution is a graph-based method for exact extraction of draining veins which, in combination with our earlier work on AVM detection, allows the AVM decomposition into veins, arteries and the nidus (with an emphasis on the draining veins). We validate the proposed approach on blood vessel phantoms representing the veins and the AVM structure, as well as on cerebral 3D digital rotational angiography (3DRA) images before and after embolization, paired with digital subtraction angiography (DSA) images. Results on AVM delineation show high correspondence to the ground truth structures and indicate potentials for use in surgical planning.
Keywords
Image skeletonization, Image segmentation, Arteriovenous malformation delineation, 3D rotational angiography, Medical image analysis

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Chicago
Babin, Danilo, Aleksandra Pizurica, Lazar Velicki, Vladimir Matić, Irena Galić, Hrvoje Leventić, Vladimir Zlokolica, and Wilfried Philips. 2018. “Skeletonization Method for Vessel Delineation of Arteriovenous Malformation.” Computers in Biology and Medicine  93: 93–105.
APA
Babin, D., Pizurica, A., Velicki, L., Matić, V., Galić, I., Leventić, H., Zlokolica, V., et al. (2018). Skeletonization method for vessel delineation of arteriovenous malformation. COMPUTERS IN BIOLOGY AND MEDICINE  , 93, 93–105.
Vancouver
1.
Babin D, Pizurica A, Velicki L, Matić V, Galić I, Leventić H, et al. Skeletonization method for vessel delineation of arteriovenous malformation. COMPUTERS IN BIOLOGY AND MEDICINE  . Elsevier BV; 2018;93:93–105.
MLA
Babin, Danilo, Aleksandra Pizurica, Lazar Velicki, et al. “Skeletonization Method for Vessel Delineation of Arteriovenous Malformation.” COMPUTERS IN BIOLOGY AND MEDICINE  93 (2018): 93–105. Print.
@article{8546392,
  abstract     = {Cerebral arteriovenous malformation (AVM) presents a great health threat due to its high probability of rupture that can cause severe brain damage. Image segmentation alone is not sufficient to support AVM embolization procedure. In order to successfully navigate the catheter and perform embolization, the segmented blood vessels need to be classified into feeding arteries, draining veins and the AVM nidus. For this reason we address here the AVM localization and vessel decomposition problem. We propose in this paper a novel AVM localization and vessel delineation method using ordered thinning-based skeletonization. The main focus of vessel delineation is the delineation of draining veins since it is essential for the embolization procedure. The main contribution is a graph-based method for exact extraction of draining veins which, in combination with our earlier work on AVM detection, allows the AVM decomposition into veins, arteries and the nidus (with an emphasis on the draining veins). We validate the proposed approach on blood vessel phantoms representing the veins and the AVM structure, as well as on cerebral 3D digital rotational angiography (3DRA) images before and after embolization, paired with digital subtraction angiography (DSA) images. Results on AVM delineation show high correspondence to the ground truth structures and indicate potentials for use in surgical planning.},
  author       = {Babin, Danilo and Pizurica, Aleksandra and Velicki, Lazar and Mati\'{c}, Vladimir and Gali\'{c}, Irena and Leventi\'{c}, Hrvoje and Zlokolica, Vladimir and Philips, Wilfried},
  issn         = {0010-4825},
  journal      = {COMPUTERS IN BIOLOGY AND MEDICINE                    },
  keyword      = {Image skeletonization,Image segmentation,Arteriovenous malformation delineation,3D rotational angiography,Medical image analysis},
  language     = {eng},
  pages        = {93--105},
  publisher    = {Elsevier BV},
  title        = {Skeletonization method for vessel delineation of arteriovenous malformation},
  url          = {http://dx.doi.org/10.1016/j.compbiomed.2017.12.011},
  volume       = {93},
  year         = {2018},
}

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