[1] HAMMAND S, HOEFME S, FRIEBEL A, et al. Three-dimensional reconstruction and quantification of key features of liver microarchitecture[J]. Zeitschrift für Gastroenterologie, 2015, 53(1):1161-1183 [2] 张翡, 范虹. 基于模糊C均值聚类的医学图像分割研究[J]. 计算机工程与应用, 2014, 50(4):144-151. (ZHANG F, FAN H. Research on medical image segmentation based on fuzzy C-means clustering algorithm[J]. Computer Engineering and Applications, 2014, 50(4):144-151.) [3] MHARIB A M, RAMLI A R, MASHOHOR S, et al. Survey on liver CT image segmentation methods[J]. Artificial Intelligence Review, 2012, 37(2):83-95. [4] HEIMANN T, van GINNEKEN B, STYNER M A, et al. Comparison and evaluation of methods for liver segmentation from CT datasets[J]. IEEE Transactions on Medical Imaging, 2009, 28(8):1251-1265. [5] SARKAR J P, SAHA I, MAULIK U. Rough possibilistic type-2 fuzzy C-means clustering for MR brain image segmentation[J]. Applied Soft Computing, 2016, 46:527-536. [6] VELMURUGAN T, MAHALAKSHMI S. Efficiency of fuzzy C means algorithm for brain tumor segmentation in MR brain images[J]. International Journal of Engineering and Technology, 2016, 8(6):2979-2989. [7] CHAIRA T. A novel intuitionistic fuzzy C means clustering algorithm and its application to medical images[J]. Applied Soft Computing, 2011, 11(2):1711-1717. [8] AHMED M N, YAMANY S M, MOHAMED N, et al. A modified fuzzy C-means algorithm for bias field estimation and segmentation of MRI data[J]. IEEE Transactions on Medical Imaging, 2002, 21(3):193-199. [9] CHEN S, ZHANG D. Robust image segmentation using FCM with spatial constraints based on new kernel-induced distance measure[J]. IEEE Transactions on Systems, Man and Cybernetics, Part B:Cybernetics, 2004, 34(4):1907-1916. [10] ZHENG J, ZHANG D, HUANG K, et al. Adaptive image segmentation method based on the fuzzy C-means with spatial information[J]. IET Image Processing, 2018, 12(5):785-792. [11] LI M, ZHANG L, XIANG Z, et al. An improved fuzzy C-means algorithm for brain MRI image segmentation[C]//Proceedings of the 2016 International Conference on Progress in Informatics & Computing. Piscataway:IEEE, 2016:336-339. [12] BEZDEK J C. A convergence theorem for the fuzzy ISODATA clustering algorithm[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1980, PAMI-2(1):1-8. [13] DEMPSTER A P, LAIRD N M, RUBIN D B. Maximum likelihood from incomplete data via the EM algorithm[J]. Journal of Royal Statistical, Series B (Methodological), 1977, 39(1):1-38. [14] KAMARUJJAMAN, MAITRA M. 3D unsupervised modified spatial fuzzy C-means method for segmentation of 3D brain MR image[J]. Pattern Analysis and Applications, 2019, 22(4):1561-1571. [15] LIEW A W C, LEUNG S H, LAU W H, et al. Fuzzy image clustering incorporating spatial continuity[J]. IEE Proceedings-Vision, Image and Signal Processing, 2000, 147(2):185-192. [16] JI Z, XIA Y, SUN Q, et al. Interval-valued possibilistic fuzzy C-means clustering algorithm[J]. Fuzzy Sets and Systems, 2014, 253:138-156. [17] KRINIDIS S, CHATZIS V. A robust fuzzy local information C-means clustering algorithm[J]. IEEE Transactions on Image Processing, 2010, 19(5):1328-1337. |