Interest-Based Ordering for Fuzzy Morphology on White Blood Cell Image Segmentation
Chastine Fatichah*,**, Martin Leonard Tangel*,
Muhammad Rahmat Widyanto***, Fangyan Dong*,
and Kaoru Hirota*
*Dept. Computational Intelligence & Systems Science, Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan
**Informatics Department, Faculty of Technology Information, Institut Teknologi Sepuluh Nopember, Kampus ITS Surabaya 60111 Indonesia
***Faculty of Computer Science, University of Indonesia, Kampus UI Depok, Jawa Barat, Indonesia
-  N. Guo, L. Zeng, and Q. Wu, “A Method based on Multispectral Imaging Technique for White Blood Cell Segmentation,” Computers in Biology and Medicine, Vol.37, pp. 70-76, 2006.
-  S. Eom, S. Kim, V. Shin, and B. Ahn, “Leukocyte Segmentation in Blood Smear Images Using Region-Based Active Contours,” Lectures Notes in Computer Science, LNCS(4179), pp. 867-876, 2006.
-  L. B. Dorini, R. Minetto, and N. J. Leite, “White blood cell segmentation using morphological operators and scale-space analysis,” Brazilian Symposium on Computer Graphics & Image Processing (SIBGRAPI), pp. 294-304, 2007.
-  K. Jiang, Q. Liao, and S. Dai, “A Novel White Blood Cell Segmentation Scheme Using Scale-Space Filtering And Watershed Clustering,” Proc. of the Second Int. Conf. on Machine Learning and Cybernetics, Xian, pp. 2820-2825, 2003.
-  N. Theera-Umpon, “White Blood Cell Segmentation and Classification in Microscopic Bone Marrow Images,” Springer-Verlag Berlin Heidelberg, pp. 787-796, 2005.
-  L. Yang, P. Meer, and D. J. Foran, “Unsupervised Segmentation Based on Robust Estimation and Color Active Contour Models,” IEEE Trans. on Information Technology in Biomedicine, Vol.9, No.3, pp. 475-486, 2005.
-  F. Zamani and R. Safabakhsh, “An unsupervised GVF Snake Approach for White Blood Cell Segmentation based on Nucleus,” ICSP2006 Proc., 2006.
-  C. Pan, Y. Fang, X. Yan, and C. Zheng, “Robust Segmentation for Low Quality Cell Images from Blood and Bone Marrow,” Int. J. of Control, Automation, and Systems, Vol.4, No.5, pp. 637-644, 2006.
-  S. Colantonio, O. Salvetti, and I. B. Gurevich, “A two-step approach for automatic microscopic image segmentation using fuzzy clustering and Neural Discrimination,” Pattern Recognition and Image Analysis, Vol.17, No.3, pp. 428-437, Pleiades Publishing, Ltd., 2007.
-  B. Ko, M. Seo, and J. Nam, “Microscopic Cell Nuclei Segmentation Based on Adaptive Attention Window,” J. of Digital Imaging, Vol.22, No.3, pp. 259-274, Springer, 2009.
-  C. Reta, L. Altamirano, J. A. Gonzalez, R. Diaz, and J. S. Guichard, “Segmentation of Bone Marrow Cell Images for Morphological Classification of Acute Leukemia,” Proc. of the Twenty-Third Int. Florida Artificial Intelligence Research Society Conf. (FLAIRS), 2010.
-  T. Deng and H. Heijmans, “Grey-scale Morphology Based on Fuzzy Logic,” J. of Mathematical Imaging and Vision, Springer Netherlands, Vol.16, No.2, pp. 155-171, 2002.
-  A. Hanbury and J. Serra, “Mathematical Morphology in the HLS Colour Space,” Proc. of the 12th BMVC British Machine Vision Conf., Vol.II, pp. 451-460, 2001.
-  A. Ledda and W. Philips, “Majority ordering for colour mathematical morphology,” Proc. of the 13th European Signal Processing Conf. EUSIPCO2005, Antalya, Turkey, 2005.
-  R. M. Haralick, S. R. Stenberg, and X. Zhuang, “Image Analysis using Mathematical Morphology,” IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.PAMI-9, No.4, 1987.
-  D. Sinha and E. R. Dougherty, “Fuzzy Mathematical Morphology,” J. of Visual Communication and Image Representation, Vol.3, No.3, pp. 286-302, 1992.
-  I. Bloch and H. Maitre, “Fuzzy Mathematical Morphology,” Annals of Mathematics and Artificial Intelligence, Vol.10, pp. 55-84, 1994.
-  I. Bloch and H. Maitre, “Fuzzy Mathematical Morphologies: A comparative study,” Pattern Recognition, Vol.28, No.9, pp. 1341-1387, 1995.
-  B. DeBaets and E. Kerre, “The fundamentals of fuzzy mathematical morphology part 1: Basic concepts,” Int. J. of General Systems, Vol.23, pp. 155-171, 1995.
-  A. Bouchet, J. Pastore, and V. Ballarin, “Segmentation of Medical Images using Fuzzy Mathematical Morphology,” J. of Computer Science & Technology, Vol.7, No.3, pp. 256-262, 2007.
-  W. Chen, Y. Q. Shi, and G. Xuan, “Identifying computer graphics using HSV color model and statistical moments of characteristic functions,” IEEE Int. Conf. on Multimedia and Expo (ICME07), Beijing, China, July 2-5, 2007.
-  A. Asano, “Granulometry and skeleton,” Pattern Information Processing Session 9, December 2008.
-  http://www.cellavision.se/cellatlas
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.