Framelet-based algorithm for segmentation of tubular structures

Cai, Xiaohao, Chan, Raymond H., Morigi, Serena and Sgallari, Fiorella (2012) Framelet-based algorithm for segmentation of tubular structures. In, Bruckstein, Alfred M., Haar Romeny, Bart M. ter, Bronstein, Alexander M. and Bronstein, Michael M. (eds.) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6667 LNCS) Third International Conference: Scale Space and Variational Methods in Computer Vision (29/05/11 - 02/06/11) Springer Berlin, Heidelberg, pp. 411-422. (doi:10.1007/978-3-642-24785-9_35).

Abstract

Framelets have been used successfully in various problems in image processing, including inpainting, impulse noise removal, super-resolution image restoration, etc. Segmentation is the process of identifying object outlines within images. There are quite a few efficient algorithms for segmentation that depend on the partial differential equation modeling. In this paper, we apply the framelet-based approach to identify tube-like structures such as blood vessels in medical images. Our method iteratively refines a region that encloses the possible boundary or surface of the vessels. In each iteration, we apply the framelet-based algorithm to denoise and smooth the possible boundary and sharpen the region. Numerical experiments of real 2D/3D images demonstrate that the proposed method is very efficient and outperforms other existing methods.

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Contributors

Author: Xiaohao Cai

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