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Similarity Metric Learning for 2D to 3D Registration of Brain Vasculature Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Tensor Voting Extraction of Vessel Centerlines from Cerebral Angiograms

Authors : Yu Ding, Mircea Nicolescu, Dan Farmer, Yao Wang, George Bebis, Fabien Scalzo

Published in: Advances in Visual Computing

Publisher: Springer International Publishing

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Abstract

The extraction of vessel centerlines from cerebral angiograms is a prerequisite for 2D-3D reconstruction and computational fluid dynamic (CFD) simulations. Many researchers have studied vessel segmentation and centerline extraction on retinal images while less attention and efforts have been devoted to cerebral angiography images. Since cerebral angiograms consist of vessels that are much noisier because of the possible patient movement, it is often a more challenging task compared to working on retinal images. In this study, we propose a multi-scale tensor voting framework to extract the vessel centerlines from cerebral angiograms. The developed framework is evaluated on a dataset of routinely acquired angiograms and reach an accuracy of 91.75\(\%\pm 5.07\%\) during our experiments.

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Metadata
Title
Tensor Voting Extraction of Vessel Centerlines from Cerebral Angiograms
Authors
Yu Ding
Mircea Nicolescu
Dan Farmer
Yao Wang
George Bebis
Fabien Scalzo
Copyright Year
2016
Book
Advances in Visual Computing

Print ISBN: 978-3-319-50834-4

Electronic ISBN: 978-3-319-50835-1

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-50835-1_4

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