Efficient and Robust Segmentations Based on Eikonal and Diffusion PDEs

Peny, B., Unal, G.B., Slabaugh, G.G., Fang, T. & Alvino, C. V. (2006). Efficient and Robust Segmentations Based on Eikonal and Diffusion PDEs. In: N Zheng, X Jiang & X Lan (Eds.), Advances in Machine Vision, Image Processing, and Pattern Analysis. Lecture Notes in Computer Science, 4153. (pp. 339-348). Springer. ISBN 3-540-37597-X

[img]
Preview
PDF - Accepted Version
Download (1MB) | Preview

Abstract

In this paper, we present efficient and simple image segmentations based on the solution of two separate Eikonal equations, each originating from a different region. Distance functions from the interior and exterior regions are computed, and final segmentation labels are determined by a competition criterion between the distance functions. We also consider applying a diffusion partial differential equation (PDE) based method to propagate information in a manner inspired by the information propagation feature of the Eikonal equation. Experimental results are presented in a particular medical image segmentation application, and demonstrate the proposed methods.

Item Type: Book Section
Additional Information: The final publication is available at Springer via http://dx.doi.org/10.1007/11821045_36
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: School of Informatics > Department of Computing
URI: http://openaccess.city.ac.uk/id/eprint/4414

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics