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Computational and Mathematical Methods in MedicineVolume 2014 2014, Article ID 357684, 13 pages

Research Article

Key Laboratory of Optoelectronic Technology and Systems of Ministry of Education, College of Optoelectronic Engineering, Chongqing University, Chongqing 400044, China

College of Computer and Information Science, Chongqing Normal University, Chongqing 400050, China

Department of Anatomy, Third Military Medical University, Chongqing 400038, China

Received 21 March 2014; Accepted 3 June 2014; Published 7 July 2014

Academic Editor: Kumar Durai

Copyright © 2014 Xuchu Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

We propose a novel region-based geometric active contour modelthat uses region-scalable discriminant and fitting energy functional for handling the intensity inhomogeneity and weak boundary problems in medical image segmentation. The region-scalable discriminant and fitting energy functional is defined to capture the image intensity characteristics in local and global regions for driving the evolution of active contour. The discriminant term in the model aims at separating background and foreground in scalable regions while the fitting term tends to fit the intensity in these regions. This model is then transformed into a variational level set formulation with a level set regularization term for accurate computation. The new model utilizes intensity information in the local and global regions as much as possible; so it not only handles better intensity inhomogeneity, but also allows more robustness to noise and more flexible initialization in comparison to the original global region and regional-scalable based models. Experimental results for synthetic and real medical image segmentation show the advantages of the proposed method in terms of accuracy and robustness.





Autor: Xuchu Wang, Yanmin Niu, Liwen Tan, and Shao-Xiang Zhang

Fuente: https://www.hindawi.com/



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