@inproceedings{daa455b35a9d4fcca1732e2a281a1fc4,
title = "Three dimensional curvilinear structure detection using optimally oriented flux",
abstract = "This paper proposes a novel curvilinear structure detector, called Optimally Oriented Flux (OOF). OOF finds an optimal axis on which image gradients are projected in order to compute the image gradient flux. The computation of OOF is localized at the boundaries of local spherical regions. It avoids considering closely located adjacent structures. The main advantage of OOF is its robustness against the disturbance induced by closely located adjacent objects. Moreover, the analytical formulation of OOF introduces no additional computation load as compared to the calculation of the Hessian matrix which is widely used for curvilinear structure detection. It is experimentally demonstrated that OOF delivers accurate and stable curvilinear structure detection responses under the interference of closely located adjacent structures as well as image noise.",
author = "Law, \{Max W.K.\} and Chung, \{Albert C.S.\}",
year = "2008",
doi = "10.1007/978-3-540-88693-8\_27",
language = "English",
isbn = "3540886923",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
number = "PART 4",
pages = "368--382",
booktitle = "Computer Vision - ECCV 2008 - 10th European Conference on Computer Vision, Proceedings",
edition = "PART 4",
note = "10th European Conference on Computer Vision, ECCV 2008 ; Conference date: 12-10-2008 Through 18-10-2008",
}