Computer-aided diagnosis of human brain tumor through MRI: A survey and a new algorithm
暂无分享,去创建一个
Kenneth Revett | Abdel-Badeeh M. Salem | El-Sayed A. El-Dahshan | Heba M. Mohsen | K. Revett | E. El-Dahshan | H. Mohsen | A. M. Salem
[1] Shigeo Abe DrEng. Pattern Classification , 2001, Springer London.
[2] Yasser Iturria-Medina,et al. Statistical analysis of brain tissue images in the wavelet domain: Wavelet-based morphometry , 2013, NeuroImage.
[3] J. Pujari,et al. WAVELET BASED FEATURES FOR COLOR TEXTURE CLASSIFICATION WITH APPLICATION TO CBIR , 2006 .
[4] D. SELVARAJ,et al. A Review on Tissue Segmentation and Feature Extraction of MRI Brain images , 2013 .
[5] Simon Haykin,et al. Neural Networks and Learning Machines , 2010 .
[6] A. M. Salem,et al. A machine learning technique for MRI brain images , 2012, 2012 8th International Conference on Informatics and Systems (INFOS).
[7] Mohamed Abid,et al. Automated Segmentation of Brain Tumor Using Optimal Texture Features and Support Vector Machine Classifier , 2012, ICIAR.
[8] Marshkole Neelam,et al. Texture and Shape based Classification of Brain Tumors using Linear Vector Quantization , 2011 .
[9] Karuppana Gounder Somasundaram,et al. Fully automatic brain extraction algorithm for axial T2-weighted magnetic resonance images , 2010, Comput. Biol. Medicine.
[10] Sung Wook Baik,et al. Prioritization of brain MRI volumes using medical image perception model and tumor region segmentation , 2013, Comput. Biol. Medicine.
[11] Mohammad Hossein Fazel Zarandi,et al. Systematic image processing for diagnosing brain tumors: A Type-II fuzzy expert system approach , 2011, Appl. Soft Comput..
[12] Aboul Ella Hassanien,et al. Prostate boundary detection in ultrasound images using biologically-inspired spiking neural network , 2011, Appl. Soft Comput..
[13] S. Aoki,et al. Magnetic resonance , 2012, International Journal of Computer Assisted Radiology and Surgery.
[14] Yasuo Yamashita,et al. Magnetic Resonance Image Analysis for Brain CAD Systems with Machine Learning , 2012 .
[15] Madasu Hanmandlu,et al. Semi-automatic Segmentation of MRI Brain Tumor , 2009 .
[16] Q. Y. Ma,et al. MRI brain image segmentation by multi-resolution edge detection and region selection. , 2000, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.
[17] Simon X. Yang,et al. Image Segmentation Using Watershed Transform and Feed-Back Pulse Coupled Neural Network , 2005, ICANN.
[18] Mohammed Yakoob Siyal,et al. An intelligent modified fuzzy c-means based algorithm for bias estimation and segmentation of brain MRI , 2005, Pattern Recognit. Lett..
[19] Andrew R. Webb,et al. Statistical Pattern Recognition , 1999 .
[20] Meritxell Bach Cuadra,et al. A review of atlas-based segmentation for magnetic resonance brain images , 2011, Comput. Methods Programs Biomed..
[21] E Le Rumeur,et al. MRI texture analysis on texture test objects, normal brain and intracranial tumors. , 2003, Magnetic resonance imaging.
[22] Héctor Allende,et al. Modified Expectation Maximization Algorithm for MRI Segmentation , 2010, CIARP.
[23] I. Jolliffe. Principal Component Analysis , 2002 .
[24] A. Kharrat,et al. A Hybrid Approach for Automatic Classification of Brain MRI Using Genetic Algorithm and Support Vector Machine , 2010 .
[25] Khizar Hayat,et al. MRI Segmentation through Wavelets and Fuzzy C-Means , 2011 .
[26] Amitava Chatterjee,et al. Hybrid multiresolution Slantlet transform and fuzzy c-means clustering approach for normal-pathological brain MR image segregation. , 2008, Medical engineering & physics.
[27] Wilhelm Burger,et al. Digital Image Processing - An Algorithmic Introduction using Java , 2008, Texts in Computer Science.
[28] Daisuke Yamamoto,et al. Computer-aided detection of multiple sclerosis lesions in brain magnetic resonance images: False positive reduction scheme consisted of rule-based, level set method, and support vector machine , 2010, Comput. Medical Imaging Graph..
[29] Daisuke Yamamoto,et al. Computer-Aided Diagnosis Systems for Brain Diseases in Magnetic Resonance Images , 2009, Algorithms.
[30] Anil K. Jain,et al. Statistical Pattern Recognition: A Review , 2000, IEEE Trans. Pattern Anal. Mach. Intell..
[31] Qiang Chen,et al. Generalized rough fuzzy c-means algorithm for brain MR image segmentation , 2012, Comput. Methods Programs Biomed..
[32] Reinhard Eckhorn,et al. Feature Linking via Synchronization among Distributed Assemblies: Simulations of Results from Cat Visual Cortex , 1990, Neural Computation.
[33] Rajeswari Ramasamy,et al. Brain Tissue Classification of MR Images Using Fast Fourier Transform Based Expectation- Maximization Gaussian Mixture Model , 2011 .
[34] Ghazanfar Latif,et al. Classification and segmentation of brain tumor using texture analysis , 2010 .
[35] Wen-Hung Chao,et al. utomatic segmentation of magnetic resonance images sing a decision tree with spatial information , 2009 .
[36] Miin Shen Yang,et al. Segmentation techniques for tissue differentiation in MRI of ophthalmology using fuzzy clustering algorithms. , 2002, Magnetic resonance imaging.
[37] Wiro J. Niessen,et al. Multi-spectral brain tissue segmentation using automatically trained k-Nearest-Neighbor classification , 2007, NeuroImage.
[38] Li-Hong Juang,et al. MRI brain lesion image detection based on color-converted K-means clustering segmentation , 2010 .
[39] Fi-John Chang,et al. Estimation of riverbed grain-size distribution using image-processing techniques , 2012 .
[40] Shohreh Kasaei,et al. Automatic Brain Tissue Detection in Mri Images Using Seeded Region Growing Segmentation and Neural Network Classification , 2011 .
[41] Sivapalan Selvadurai,et al. Ethnic attitudes, political preferences and the politics of stability , 2011 .
[42] Juan Manuel Górriz,et al. Two fully-unsupervised methods for MR brain image segmentation using SOM-based strategies , 2013, Appl. Soft Comput..
[43] Nan Zhang,et al. Kernel feature selection to fuse multi-spectral MRI images for brain tumor segmentation , 2011, Comput. Vis. Image Underst..
[44] Amitava Chatterjee,et al. A Slantlet transform based intelligent system for magnetic resonance brain image classification , 2006, Biomed. Signal Process. Control..
[45] Vinod Kumar,et al. A novel content-based active contour model for brain tumor segmentation. , 2012, Magnetic resonance imaging.
[46] Farzad Towhidkhah,et al. A novel method for automatic determination of different stages of multiple sclerosis lesions in brain MR FLAIR images , 2008, Comput. Medical Imaging Graph..
[47] Radu Orghidan,et al. A Hybrid 3D Learning-and-Interaction-based Segmentation Approach Applied on CT Liver Volumes , 2013 .
[48] Abdel-Badeeh M. Salem,et al. Hybrid intelligent techniques for MRI brain images classification , 2010, Digit. Signal Process..
[49] Maqsood Mahmud,et al. MR imaging enhancement and segmentation of tumor using fuzzy curvelet , 2011 .
[50] Christos Davatzikos,et al. Classification of brain tumor type and grade using MRI texture and shape in a machine learning scheme , 2009, Magnetic resonance in medicine.
[51] Christopher M. Brown,et al. Progressive Livewire for Automatic Contour Extraction , 2004 .
[52] T. Logeswari,et al. An Improved Implementation of Brain Tumor Detection Using Segmentation Based on Hierarchical Self Organizing Map , 2010 .
[53] Andrea Schenone,et al. A fuzzy clustering based segmentation system as support to diagnosis in medical imaging , 1999, Artif. Intell. Medicine.
[54] Inan Güler,et al. Combining stationary wavelet transform and self-organizing maps for brain MR image segmentation , 2011, Eng. Appl. Artif. Intell..
[55] Abdul Hanan Abdullah,et al. The Impact of Information and Communication Technologies on Developing Countries , 2011 .
[56] Zhenyu Zhou,et al. Multicontext wavelet-based thresholding segmentation of brain tissues in magnetic resonance images. , 2007, Magnetic resonance imaging.
[57] Wen-Hung Chao,et al. Improving segmentation accuracy for magnetic resonance imaging using a boosted decision tree , 2008, Journal of Neuroscience Methods.
[58] Kaliyil Janardhan Shanthi,et al. Neuro-Fuzzy Approach Toward Segmentation of Brain MRI Based on Intensity and Spatial Distribution. , 2010, Journal of medical imaging and radiation sciences.
[59] David G. Stork,et al. Pattern Classification , 1973 .
[60] Shi Weili,et al. Research of automatic medical image segmentation algorithm based on Tsallis entropy and improved PCNN , 2009, 2009 International Conference on Mechatronics and Automation.
[61] Jason M. Kinser,et al. Image Processing using Pulse-Coupled Neural Networks , 1998, Perspectives in Neural Computing.
[62] Vladimir Cherkassky,et al. Learning from Data: Concepts, Theory, and Methods , 1998 .
[63] Sanjay Sharma,et al. Brain Tumor Detection based on Multi-parameter MRI Image Analysis , 2009 .
[64] Ling Zhang,et al. Automated breast cancer detection and classification using ultrasound images: A survey , 2015, Pattern Recognit..
[65] Биология. Laboratory of Neuro Imaging , 2010 .
[66] Mehdi Chehel Amirani,et al. A Robust Brain MRI Classification with GLCM Features , 2012 .
[67] Ingrid Daubechies,et al. Ten Lectures on Wavelets , 1992 .
[68] G. Grisetti,et al. Further Reading , 1984, IEEE Spectrum.
[69] Zohreh Azimifar,et al. Brain volumetry: An active contour model-based segmentation followed by SVM-based classification , 2011, Comput. Biol. Medicine.
[70] John L. Johnson,et al. Stabilized input with a feedback pulse‐coupled neural network , 1996 .
[71] Frank G Zöllner,et al. SVM-based glioma grading: Optimization by feature reduction analysis. , 2012, Zeitschrift fur medizinische Physik.
[72] R. Dhanasekaran,et al. Fuzzy Clustering and Deformable Model for Tumor Segmentation on MRI Brain Image: A Combined Approach , 2012 .
[73] Reza Azmi,et al. Brain tissue segmentation in MR images based on a hybrid of MRF and social algorithms , 2012, Medical Image Anal..
[74] Andrés Ortiz,et al. Improving MRI segmentation with probabilistic GHSOM and multiobjective optimization , 2013, Neurocomputing.
[75] Jonathan Lawry,et al. Symbolic and Quantitative Approaches to Reasoning with Uncertainty , 2009 .
[76] Esa Alhoniemi,et al. Gaussian mixture model-based segmentation of MR images taken from premature infant brains , 2009, Journal of Neuroscience Methods.
[77] Robert A. Lordo,et al. Learning from Data: Concepts, Theory, and Methods , 2001, Technometrics.
[78] Baowei Fei,et al. A modified fuzzy C-means classification method using a multiscale diffusion filtering scheme , 2009, Medical Image Anal..
[79] P. Mathurin,et al. [Magnetic resonance imaging of the brain]. , 1988, Journal belge de radiologie.
[80] Nahla Ben Amor,et al. Brain Tumor Segmentation Using Support Vector Machines , 2009, ECSQARU.
[81] Yasuo Yamashita,et al. Automated detection of multiple sclerosis candidate regions in MR images: false-positive removal with use of an ANN-controlled level-set method , 2011, Radiological Physics and Technology.
[82] George C. Kagadis,et al. Improving brain tumor characterization on MRI by probabilistic neural networks and non-linear transformation of textural features , 2008, Comput. Methods Programs Biomed..
[83] Lalit M. Patnaik,et al. Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network , 2006, Biomed. Signal Process. Control..
[84] Stephen T. C. Wong,et al. Image segmentation by EM-based adaptive pulse coupled neural networks in brain magnetic resonance imaging , 2010, Comput. Medical Imaging Graph..
[85] Xiangrong Zhou,et al. Computer-aided diagnosis: The emerging of three CAD systems induced by Japanese health care needs , 2008, Comput. Methods Programs Biomed..
[86] Yudong Zhang,et al. A hybrid method for MRI brain image classification , 2011, Expert Syst. Appl..
[87] A. Besga,et al. Computer Aided Diagnosis system for Alzheimer Disease using brain Diffusion Tensor Imaging features selected by Pearson's correlation , 2011, Neuroscience Letters.
[88] Mohamed Abid,et al. Medical Image Classification Using an Optimal Feature Extraction Algorithm and a Supervised Classifier Technique , 2011, Int. J. Softw. Sci. Comput. Intell..
[89] D. Selvathi,et al. Brain MRI Slices Classification Using Least Squares Support Vector Machine , 2007 .
[90] Hyung Woo Kang,et al. G-wire: A livewire segmentation algorithm based on a generalized graph formulation , 2005, Pattern Recognit. Lett..
[91] Yudong Zhang,et al. A Novel Method for Magnetic Resonance Brain Image Classification Based on Adaptive Chaotic PSO , 2010 .
[92] Abdul Rahman Ramli,et al. Medical Image Segmentation Using Fuzzy C-Mean (FCM), Learning Vector Quantization (LVQ) and User Interaction , 2008, ICIC.