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Computational and Mathematical Methods in Medicine
Volume 2015 (2015), Article ID 185726, 14 pages
http://dx.doi.org/10.1155/2015/185726
Research Article

Research on a Pulmonary Nodule Segmentation Method Combining Fast Self-Adaptive FCM and Classification

1School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan 250014, China
2Digital Media Technology Key Lab of Shandong Province, Jinan 250014, China
3Lawrence Berkeley National Lab, University of California, Berkeley, CA 94720, USA
4Respiratory Department, Shandong Provincial Qianfoshan Hospital, Jinan 250014, China

Received 9 April 2014; Revised 1 November 2014; Accepted 21 December 2014

Academic Editor: William Crum

Copyright © 2015 Hui Liu 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.

How to Cite this Article

Hui Liu, Cai-Ming Zhang, Zhi-Yuan Su, Kai Wang, and Kai Deng, “Research on a Pulmonary Nodule Segmentation Method Combining Fast Self-Adaptive FCM and Classification,” Computational and Mathematical Methods in Medicine, vol. 2015, Article ID 185726, 14 pages, 2015. doi:10.1155/2015/185726