relation: https://openaccess.city.ac.uk/id/eprint/4414/
title: Efficient and Robust Segmentations Based on Eikonal and Diffusion PDEs
creator: Peny, B.
creator: Unal, G. B.
creator: Slabaugh, G. G.
creator: Fang, T.
creator: Alvino, C. V.
subject: QA75 Electronic computers. Computer science
description: 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.
publisher: Springer
contributor: Zheng, N
contributor: Jiang, X
contributor: Lan, X
date: 2006
type: Book Section
type: PeerReviewed
format: application/pdf
language: en
identifier: https://openaccess.city.ac.uk/id/eprint/4414/1/PDEsIWICPAS2006.pdf
identifier:   Peny, B., Unal, G. B., Slabaugh, G. G. , Fang, T. & Alvino, C. V.view all authorsEPJS_limit_names_shown_load( 'creators_name_4414_et_al', 'creators_name_4414_rest' ); (2006). Efficient and Robust Segmentations Based on Eikonal and Diffusion PDEs. In: Zheng, N, Jiang, X & Lan, X  (Eds.), Advances in Machine Vision, Image Processing, and Pattern Analysis. Lecture Notes in Computer Science, 4153.  (pp. 339-348). Springer. doi: 10.1007/11821045_36 <https://doi.org/10.1007/11821045_36>  
relation: http://dx.doi.org/10.1007/11821045_36
relation: 10.1007/11821045_36
identifier: 10.1007/11821045_36