[1]
Pal N R and Pal S K. A review on image segmentation techniques. Pattern Recognition, 1993, 26(9): 1277-1294.
DOI: 10.1016/0031-3203(93)90135-j
Google Scholar
[2]
Xin Liu, Langer, D.L., Haider, M.A., Yang, Y., Wernick, M. N, Yetik, I.S. Prostate cancer segmentation with simultaneous estimation of Markov Random Field parameters and class. IEEE Trans. on Medical Imaging. 2009, 28(6): 906-915.
DOI: 10.1109/tmi.2009.2012888
Google Scholar
[3]
Ahmed, M.N.; Yamany, S.M.; Mohamed, N.; Farag, A.A.; Moriarty, T., A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data. IEEE Trans. on Medical Imaging. 2002, 21(3): 193-199.
DOI: 10.1109/42.996338
Google Scholar
[4]
Sahoo P K, Soltani S and Wong K C, et al. A survey of threshold in techniques. Computer Vision, Graphics, and Image Processing, 1988, 41(2): 233-260.
DOI: 10.1016/0734-189x(88)90022-9
Google Scholar
[5]
Otsu N. A threshold selection method from gray-level histograms. IEEE Transactions on System Man and Cybernetic, 1979, 9(1): 62-66.
DOI: 10.1109/tsmc.1979.4310076
Google Scholar
[6]
Zhiwei Tang and Yixuan Wu. One image segmentation method based on Otsu and fuzzy theory seeking image segment threshold, 2011 International Conference on Electronics, Communications and Control, Ningbo, 2011: 2170-2173.
DOI: 10.1109/icecc.2011.6066573
Google Scholar
[7]
R M Haralick and L G Shapiro. Image segmentation techniques. Computer vision,graphics,and image processing, 1985, 29: 100-132.
DOI: 10.1016/s0734-189x(85)90153-7
Google Scholar
[8]
Pohle R, and Toennies K D, A new approach for model based adaptive region growing in medical image analysis,. Proc of the 9th International Conference on Computer Analysis and Patterns, Warsaw Poland, 2001: 238-243.
DOI: 10.1007/3-540-44692-3_30
Google Scholar
[9]
Daw-Tung Lin, Chung-Chih Lei and Siu-Wan Hung. Computer-aided kidney segmentation on abdominal CT images. IEEE Transactions on Information Technology in Biomedicine, 2006, 10(1): 59-65.
DOI: 10.1109/titb.2005.855561
Google Scholar
[10]
Vincent L and Soille P. Watersheds in digital spaces: an efficient algorithm based on immersion simulations. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1991, 13(6): 583- 598.
DOI: 10.1109/34.87344
Google Scholar
[11]
Lescure P, Yedid V M and Dupoisot H, et al. Color segmentation on biological microscope images,. Application of Artificial Neural Networks in Image Processing IV, San Jose, California, USA, 1999: 182~193.
DOI: 10.1117/12.341119
Google Scholar
[12]
Sang Do-Thanh, Woo Dong-Min and Park Dong-Chul. Centroid neural network with simulated annealing and its application to color image segmentation,. 19th International Conference on Neural Information Processing, ICONIP 2012, Doha, Qatar, 2012, 3: 1-8.
DOI: 10.1007/978-3-642-34487-9_1
Google Scholar
[13]
Bhattacharyya Siddhartha, Maulik Ujjwal and Dutta Paramartha. A parallel bi-directional self-organizing neural network (PBDSONN) architecture for color image extraction and segmentation. Neurocomputing, 2012, 86: 1-23.
DOI: 10.1016/j.neucom.2011.11.025
Google Scholar
[14]
Kass M, Witkin A and Terzopoulos D. Snakes: active contour models. International Journal of Computer Vision, 1987, 1(4): 321- 331.
DOI: 10.1007/bf00133570
Google Scholar
[15]
Osher S and Sethian J. Fronts propagating with curvature-dependent speed: algorithms based on the Hamilton Jacobi formulation. Journal of Computational Physics, 1988, 79(1): 12-49.
DOI: 10.1016/0021-9991(88)90002-2
Google Scholar
[16]
Cohen L D. On active contour models and balloons. CVGIP: Image Understanding, 1991, 53 (2):211-218.
DOI: 10.1016/1049-9660(91)90028-n
Google Scholar
[17]
Chenyang Xu and Jerry L. Snakes, shapes, and gradient vector flow. IEEE Transactions on Image Processing, 1998, 7(3): 359-369.
DOI: 10.1109/83.661186
Google Scholar
[18]
Menet S, Saint-Mar P and Medion G. B-Snakes:implementation and application to stereo,. Artificial Intelligence and Computer Vision. Proceedings of the Seventh Israeli Conference, Ramat Gan, Israel 1991, 223-236.
Google Scholar
[19]
Cham T J and Cipolla R. Stereo coupled active contours, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Juan, Puerto Rico, 1997: 1094-1099.
DOI: 10.1109/cvpr.1997.609466
Google Scholar
[20]
Barat C and Lagadec B. A corner tracker snake approach to segment irregular object shape in video image,. IEEE International Conference on Acoustic, Speech and Signal Processes, Las Vegas, NV, USA 2008: 717-720.
DOI: 10.1109/icassp.2008.4517710
Google Scholar
[21]
Celeux G, Forbes F, Peyrard N. EM procedures using mean field-like approximations for Markov model-based image segmentation. Pattern Recognition, 2003, 36(1): 131-144.
DOI: 10.1016/s0031-3203(02)00027-4
Google Scholar