Automated Feature Extraction in Brain Tumor by Magnetic Resonance Imaging Using Gaussian Mixture Models
暂无分享,去创建一个
[1] Timothy D Johnson,et al. Functional diffusion map as an early imaging biomarker for high-grade glioma: correlation with conventional radiologic response and overall survival. , 2008, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[2] Richard Gran,et al. On the Convergence of Random Search Algorithms In Continuous Time with Applications to Adaptive Control , 1970, IEEE Trans. Syst. Man Cybern..
[3] Vinod Kumar,et al. Segmentation, Feature Extraction, and Multiclass Brain Tumor Classification , 2013, Journal of Digital Imaging.
[4] Donald F. Specht,et al. Probabilistic neural networks , 1990, Neural Networks.
[5] M. Stone. Cross‐Validatory Choice and Assessment of Statistical Predictions , 1976 .
[6] Deepa Subramaniam Nachimuthu,et al. Multidimensional Texture Characterization: On Analysis for Brain Tumor Tissues Using MRS and MRI , 2014, Journal of Digital Imaging.
[7] F. Cendes,et al. Texture analysis of medical images. , 2004, Clinical radiology.
[8] Ιωάννης Καλατζής,et al. Improving brain tumor characterization on MRI by probabilistic neural networks and non-linear transformation of textural features , 2015 .
[9] Stéphane Mallat,et al. A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..
[10] N Kumaravel,et al. A wavelet-based optimal texture feature set for classification of brain tumours , 2008, Journal of medical engineering & technology.
[11] Andreas Christmann,et al. Support vector machines , 2008, Data Mining and Knowledge Discovery Handbook.
[12] Samy Bengio,et al. User authentication via adapted statistical models of face images , 2006, IEEE Transactions on Signal Processing.
[13] Asoke K. Nandi,et al. Detection of masses in mammograms via statistically based enhancement, multilevel-thresholding segmentation, and region selection , 2008, Comput. Medical Imaging Graph..
[14] Bradley James Erickson,et al. Part 1. Automated Change Detection and Characterization in Serial MR Studies of Brain-Tumor Patients , 2007, Journal of Digital Imaging.
[15] N. Otsu. A threshold selection method from gray level histograms , 1979 .
[16] Perry W. Grigsby,et al. Temporal analysis of intratumoral metabolic heterogeneity characterized by textural features in cervical cancer , 2013, European Journal of Nuclear Medicine and Molecular Imaging.
[17] A. Dandache,et al. Improving of colon cancer cells detection based on Haralick's features on segmented histopathological images , 2011, 2011 IEEE International Conference on Computer Applications and Industrial Electronics (ICCAIE).
[18] Ingrid Daubechies,et al. Ten Lectures on Wavelets , 1992 .
[19] Ralf Klinkenberg,et al. Data Classification: Algorithms and Applications , 2014 .
[20] Rivka R Colen,et al. Imaging genomic mapping in glioblastoma. , 2013, Neurosurgery.
[21] J. Barnholtz-Sloan,et al. CBTRUS statistical report: Primary brain and central nervous system tumors diagnosed in the United States in 2006-2010. , 2013, Neuro-oncology.
[22] Ferenc A. Jolesz,et al. Radiogenomic Mapping of Edema/Cellular Invasion MRI-Phenotypes in Glioblastoma Multiforme , 2011, PloS one.
[23] Shutao Li,et al. Wavelet-Based Feature Extraction for Microarray Data Classification , 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.
[24] Doaa Mahmoud-Ghoneim,et al. The impact of image dynamic range on texture classification of brain white matter , 2008, BMC Medical Imaging.
[25] Jean-Luc Gauvain,et al. Feature and score normalization for speaker verification of cellular data , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..
[26] G. Unsgaard,et al. Effects of type beta transforming growth factor in combination with retinoic acid or tumor necrosis factor on proliferation of a human glioblastoma cell line and clonogenic cells from freshly resected human brain tumors , 2004, Cancer Immunology, Immunotherapy.
[27] Ronald W. Schafer,et al. Multilevel thresholding using edge matching , 1988, Comput. Vis. Graph. Image Process..
[28] U. Rajendra Acharya,et al. Wavelet-Based Energy Features for Glaucomatous Image Classification , 2012, IEEE Transactions on Information Technology in Biomedicine.
[29] C. Thieke,et al. Diffusion-weighted imaging-based probabilistic segmentation of high- and low-proliferative areas in high-grade gliomas , 2012, Cancer imaging : the official publication of the International Cancer Imaging Society.
[30] 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..
[31] J. Barnholtz-Sloan,et al. CBTRUS statistical report: primary brain and central nervous system tumors diagnosed in the United States in 2007-2011. , 2012, Neuro-oncology.
[32] Haizhou Li,et al. An overview of text-independent speaker recognition: From features to supervectors , 2010, Speech Commun..
[33] Ho-Ling Liu,et al. Quality Assurance of Clinical MRI Scanners Using ACR MRI Phantom: Preliminary Results , 2004, Journal of Digital Imaging.
[34] Xinbo Gao,et al. Image multi-thresholding by combining the lattice Boltzmann model and a localized level set algorithm , 2012, Neurocomputing.
[35] Ahmad Chaddad,et al. Brain tumor identification using Gaussian Mixture Model features and Decision Trees classifier , 2014, 2014 48th Annual Conference on Information Sciences and Systems (CISS).
[36] S. Gabriel,et al. Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1. , 2010, Cancer cell.
[37] Lucia Dettori,et al. A comparison of wavelet, ridgelet, and curvelet-based texture classification algorithms in computed tomography , 2007, Comput. Biol. Medicine.
[38] Abbas Dandache,et al. Carcinoma cell identification via optical microscopy and shape feature analysis , 2013 .
[39] Moeness G. Amin,et al. Gaussian mixture modeling approach for stationary human identification in through-the-wall radar imagery , 2015, J. Electronic Imaging.
[40] Jatindra Kumar Dash,et al. Wavelet based features of circular scan lines for mammographic mass classification , 2012, 2012 1st International Conference on Recent Advances in Information Technology (RAIT).
[41] Jianhua Yao,et al. Enhancing Image Analytic Tools by Fusing Quantitative Physiological Values with Image Features , 2011, Journal of Digital Imaging.
[42] J Chambron,et al. Distinct patterns of active and non-active plaques using texture analysis on brain NMR images in multiple sclerosis patients: preliminary results. , 1999, Magnetic resonance imaging.
[43] Bostjan Likar,et al. Retrospective correction of MR intensity inhomogeneity by information minimization , 2000, IEEE Transactions on Medical Imaging.
[44] J. Goo,et al. Receiver Operating Characteristic (ROC) Curve: Practical Review for Radiologists , 2004, Korean journal of radiology.
[45] 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.