Segmentation and Diagnosis of Liver Carcinoma Based on Adaptive Scale-Kernel Fuzzy Clustering Model for CT Images
Author:
Publisher
Springer Science and Business Media LLC
Subject
Health Information Management,Health Informatics,Information Systems,Medicine (miscellaneous)
Link
http://link.springer.com/content/pdf/10.1007/s10916-019-1459-2.pdf
Reference38 articles.
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3. Peng, J., Wang, Y., and Kong, D., Liver segmentation with constrained convex variational model. Pattern Recogn. Lett. 43(7):81–88, 2014.
4. Qian, P., Jiang, Y., Deng, Z., Lingzhi, H., Sun, S., Wang, S., and Muzic, Jr., R. F., Cluster prototypes and fuzzy memberships jointly leveraged cross-domain maximum entropy clustering. IEEE Transactions on Cybernetics 46(1):181–193, 2016.
5. Yang, H., and Zeng, J. H., A hierarchical local region-based sparse shape composition for liver segmentation in CT scans. Pattern Recogn. 50:88–106, 2016.
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