Hybrid intelligent approach for diagnosis of the lung nodule from CT images using spatial kernelized fuzzy c-means and ensemble learning
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Mohammad Hossein Fazel Zarandi | Abbas Ahmadi | Farzad Vasheghani Farahani | M. Zarandi | Abbas Ahmadi | F. Farahani
[1] Enrique H. Ruspini,et al. A New Approach to Clustering , 1969, Inf. Control..
[2] J. Austin,et al. Glossary of terms for CT of the lungs: recommendations of the Nomenclature Committee of the Fleischner Society. , 1996, Radiology.
[3] R. Polikar,et al. Ensemble based systems in decision making , 2006, IEEE Circuits and Systems Magazine.
[4] J. C. Dunn,et al. A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters , 1973 .
[5] Mohammad Hossein Fazel Zarandi,et al. Lung tumor area recognition in CT images based on Gustafson-Kessel clustering , 2016, 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).
[6] Enrique H. Ruspini,et al. Numerical methods for fuzzy clustering , 1970, Inf. Sci..
[7] Subhash C. Bagui,et al. Combining Pattern Classifiers: Methods and Algorithms , 2005, Technometrics.
[8] Sankar K. Pal,et al. A review on image segmentation techniques , 1993, Pattern Recognit..
[9] John A. Hartigan,et al. Clustering Algorithms , 1975 .
[10] Dzung L. Pham,et al. Fuzzy clustering with spatial constraints , 2002, Proceedings. International Conference on Image Processing.
[11] R. Devi,et al. Robust kernel FCM in segmentation of breast medical images , 2011, Expert Syst. Appl..
[12] Abbas Z. Kouzani,et al. Random forest based lung nodule classification aided by clustering , 2010, Comput. Medical Imaging Graph..
[13] Babita Pandey,et al. Knowledge and intelligent computing system in medicine , 2009, Comput. Biol. Medicine.
[14] Xiangyang Wang,et al. A fast and robust image segmentation using FCM with spatial information , 2010, Digit. Signal Process..
[15] Václav Snásel,et al. Machine Learning Techniques for Prostate Ultrasound Image Diagnosis , 2010, Advances in Machine Learning I.
[16] Stephen M. Moore,et al. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository , 2013, Journal of Digital Imaging.
[17] Jerry L Prince,et al. Current methods in medical image segmentation. , 2000, Annual review of biomedical engineering.
[18] Umi Kalthum Ngah,et al. Breast MRI Tumour Segmentation Using Modified Automatic Seeded Region Growing Based on Particle Swarm Optimization Image Clustering , 2014 .
[19] Temesguen Messay,et al. A new computationally efficient CAD system for pulmonary nodule detection in CT imagery , 2010, Medical Image Anal..
[20] Mohammad Hossein Fazel Zarandi,et al. Lung nodule diagnosis from CT images based on ensemble learning , 2015, 2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB).
[21] M.N. Mughal,et al. Early lung cancer detection by classifying chest CT images: a survey , 2004, 8th International Multitopic Conference, 2004. Proceedings of INMIC 2004..
[22] James C. Bezdek,et al. Decision templates for multiple classifier fusion: an experimental comparison , 2001, Pattern Recognit..
[23] Noboru Yanai,et al. Prognosis of non-surgically treated, clinical stage I lung cancer patients in Japan. , 2002, Lung cancer.
[24] Abbas Z. Kouzani,et al. Automated detection of lung nodules in computed tomography images: a review , 2010, Machine Vision and Applications.
[25] Zohreh Azimifar,et al. Lung nodule segmentation and recognition using SVM classifier and active contour modeling: A complete intelligent system , 2013, Comput. Biol. Medicine.
[26] Bram van Ginneken,et al. Computer analysis of computed tomography scans of the lung: a survey , 2006, IEEE Transactions on Medical Imaging.
[27] Amparo Alonso-Betanzos,et al. Analysis and evaluation of hard and fuzzy clustering segmentation techniques in burned patient images , 2000, Image Vis. Comput..
[28] Abbas Ahmadi,et al. Simulation-based optimization of radiotherapy: Agent-based modeling and reinforcement learning , 2017, Math. Comput. Simul..
[29] A. H. El-Baz,et al. Hybrid intelligent system-based rough set and ensemble classifier for breast cancer diagnosis , 2014, Neural Computing and Applications.
[30] Amir-Masoud Eftekhari-Moghadam,et al. Knowledge discovery in medicine: Current issue and future trend , 2014, Expert Syst. Appl..
[31] Korris Fu-Lai Chung,et al. Robust fuzzy clustering-based image segmentation , 2009, Appl. Soft Comput..
[32] Sankar K. Pal,et al. Fuzzy models for pattern recognition , 1992 .
[33] Dao-Qiang Zhang,et al. A novel kernelized fuzzy C-means algorithm with application in medical image segmentation , 2004, Artif. Intell. Medicine.
[34] Feng Zhao,et al. An Adaptive Non Local Spatial Fuzzy Image Segmentation Algorithm , 2012, ICIC.
[35] O. Miettinen,et al. Early Lung Cancer Action Project: overall design and findings from baseline screening , 1999, The Lancet.
[36] Tom Fawcett,et al. ROC Graphs: Notes and Practical Considerations for Researchers , 2007 .
[37] Robin N. Strickland. Tumor detection in nonstationary backgrounds , 1994, IEEE Trans. Medical Imaging.
[38] Mohammad Hossein Fazel Zarandi,et al. Fuzzy rule based expert system for diagnosis of lung cancer , 2015, 2015 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS) held jointly with 2015 5th World Conference on Soft Computing (WConSC).
[39] Bernhard E. Boser,et al. A training algorithm for optimal margin classifiers , 1992, COLT '92.
[40] A. Ramli,et al. Computer-aided detection/diagnosis of breast cancer in mammography and ultrasound: a review. , 2013, Clinical imaging.
[41] S. R. Kannan,et al. A new segmentation system for brain MR images based on fuzzy techniques , 2008, Appl. Soft Comput..
[42] Hamid R. Tizhoosh,et al. Type-2 Fuzzy Image Enhancement , 2005, ICIAR.
[43] E. Hoffman,et al. Assessment of the pulmonary structure-function relationship and clinical outcomes measures: quantitative volumetric CT of the lung. , 1997, Academic radiology.
[44] Michael C. Lee,et al. Computer-aided diagnosis of pulmonary nodules using a two-step approach for feature selection and classifier ensemble construction , 2010, Artif. Intell. Medicine.
[45] Thomas G. Dietterich. Machine-Learning Research , 1997, AI Mag..
[46] Tamalika Chaira,et al. An improved medical image enhancement scheme using Type II fuzzy set , 2014, Appl. Soft Comput..
[47] Jiri Matas,et al. On Combining Classifiers , 1998, IEEE Trans. Pattern Anal. Mach. Intell..
[48] Guillaume Lemaitre,et al. Computer-Aided Detection and diagnosis for prostate cancer based on mono and multi-parametric MRI: A review , 2015, Comput. Biol. Medicine.
[49] Patrick Haffner,et al. Support vector machines for histogram-based image classification , 1999, IEEE Trans. Neural Networks.
[50] Ehsanollah Kabir,et al. A subspace approach to error correcting output codes , 2013, Pattern Recognit. Lett..
[51] Safdar Ali,et al. Prediction of human breast and colon cancers from imbalanced data using nearest neighbor and support vector machines , 2014, Comput. Methods Programs Biomed..
[52] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[53] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[54] Aly A. Farag,et al. A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data , 2002, IEEE Transactions on Medical Imaging.
[55] Kurt Hornik,et al. Multilayer feedforward networks are universal approximators , 1989, Neural Networks.
[56] Mohammad Hossein Fazel Zarandi,et al. A new multiple classifier system for diagnosis of erythemato-squamous diseases based on rough set feature selection , 2016, 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).
[57] Marcelo Gattass,et al. Automatic segmentation of lung nodules with growing neural gas and support vector machine , 2012, Comput. Biol. Medicine.
[58] James C. Bezdek,et al. Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.
[59] Anil K. Jain. Data clustering: 50 years beyond K-means , 2010, Pattern Recognit. Lett..
[60] A. Akan,et al. A novel approach to malignant-benign classification of pulmonary nodules by using ensemble learning classifiers , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[61] S. R. Kannan,et al. Effective fuzzy c-means based kernel function in segmenting medical images , 2010, Comput. Biol. Medicine.
[62] Matthew T. Freedman,et al. Artificial convolution neural network techniques and applications for lung nodule detection , 1995, IEEE Trans. Medical Imaging.
[63] Richard C. Pais,et al. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): a completed reference database of lung nodules on CT scans. , 2011, Medical physics.
[64] K. Gunavathi,et al. Lung cancer classification using neural networks for CT images , 2014, Comput. Methods Programs Biomed..
[65] Russell C. Hardie,et al. Performance analysis of a new computer aided detection system for identifying lung nodules on chest radiographs , 2008, Medical Image Anal..