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.
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Peny, B., Unal, G., Slabaugh, G., Fang, T., Alvino, C. (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. IWICPAS 2006. Lecture Notes in Computer Science, vol 4153. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11821045_36
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DOI: https://doi.org/10.1007/11821045_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37597-5
Online ISBN: 978-3-540-37598-2
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