Image segmentation by fuzzy and possibilistic clustering algorithms for the identification of microcalcifications

[1]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[2]  J. MacQueen.  Some methods for classification and analysis of multivariate observations , 1967 .

[3]  J. C. Dunn,et al.  A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters , 1973 .

[4]  F. Meyer.  Iterative image transformations for an automatic screening of cervical smears. , 1979, The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society.

[5]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.

[6]  Ian W. Ricketts,et al.  The Mammographic Image Analysis Society digital mammogram database , 1994 .

[7]  William R. Brody,et al.  Segmentation algorithms for detecting microcalcifications in mammograms , 1997, IEEE Transactions on Information Technology in Biomedicine.

[8]  James C. Bezdek,et al.  A mixed c-means clustering model , 1997, Proceedings of 6th International Fuzzy Systems Conference.

[9]  N. Pandey,et al.  Fuzzy logic based microcalcification detection , 2000, Neural Networks for Signal Processing X. Proceedings of the 2000 IEEE Signal Processing Society Workshop (Cat. No.00TH8501).

[10]  Antonio Vega-Corona,et al.  Feature Vectors Generation for Detection of Microcalcifications in Digitized Mammography Using Neural Networks , 2003, IWANN.

[11]  Heng-Da Cheng,et al.  Computer-aided detection and classification of microcalcifications in mammograms: a survey , 2003, Pattern Recognit..

[12]  Matteo Fraschini,et al.  Contrast enhancement of microcalcifications in mammograms using morphological enhancement and non-flat structuring elements , 2004 .

[13]  Heng-Da Cheng,et al.  Microcalcification detection using fuzzy logic and scale space approaches , 2004, Pattern Recognit..

[14]  James M. Keller,et al.  A possibilistic fuzzy c-means clustering algorithm , 2005, IEEE Transactions on Fuzzy Systems.

[15]  Jianmin Jiang,et al.  Integration of fuzzy logic and structure tensor towards mammogram contrast enhancement. , 2005, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[16]  Tao Xiong,et al.  A combined SVM and LDA approach for classification , 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

[17]  Qian Huang,et al.  Detection of Microcalcifications in Digital Mammograms Based on Dual-Threshold , 2006, Digital Mammography / IWDM.

[18]  R. Malmathanraj,et al.  Segmentation and SVM Classification of Mammograms , 2006, 2006 IEEE International Conference on Industrial Technology.

[19]  Berkman Sahiner,et al.  Computer-aided detection system for clustered microcalcifications: comparison of performance on full-field digital mammograms and digitized screen-film mammograms , 2007, Physics in medicine and biology.

[20]  M. Bhattacharya,et al.  Fuzzy Logic Based Segmentation of Microcalcification in Breast Using Digital Mammograms Considering Multiresolution , 2007, International Machine Vision and Image Processing Conference (IMVIP 2007).

[21]  Shengyong Chen,et al.  Automatic Segmentation of Micro-calcification Based on SIFT in Mammograms , 2008, 2008 International Conference on BioMedical Engineering and Informatics.

[22]  G. Veni,et al.  A New Method of Detecting Microcalcification Clusters for Computer Aided Digital Mammography , 2008, 2008 19th International Conference on Systems Engineering.

[23]  S. Mashohor,et al.  New multi-scale medical image segmentation based on fuzzy c-mean (FCM) , 2008, 2008 IEEE Conference on Innovative Technologies in Intelligent Systems and Industrial Applications.

[24]  D. Andina,et al.  Images sub-segmentation with the PFCM clustering algorithm , 2009, 2009 7th IEEE International Conference on Industrial Informatics.

[25]  Brijesh Verma.  Impact of multiple clusters on neural classification of ROIs in digital mammograms , 2009, 2009 International Joint Conference on Neural Networks.

[26]  Antonio Vega-Corona,et al.  Edges Detection of Clusters of Microcalcifications with SOM and Coordinate Logic Filters , 2009, IWANN.

[27]  Ioannis Kalatzis,et al.  Fuzzy C-means-driven FHCE contextual segmentation method for mammographic microcalcification detection , 2010 .