Automated classification of glaucoma stages using higher order cumulant features
暂无分享,去创建一个
[1] Jie Zhu,et al. Shearlet-based texture feature extraction for classification of breast tumor in ultrasound image , 2013, Biomed. Signal Process. Control..
[2] U. Rajendra Acharya,et al. ECG beat classification using PCA, LDA, ICA and Discrete Wavelet Transform , 2013, Biomed. Signal Process. Control..
[3] Yamunadevi Lakshmanan,et al. Stereoacuity in mild, moderate and severe glaucoma , 2013, Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians.
[4] Chua Kuang Chua,et al. Automated detection of optic disk in retinal fundus images using intuitionistic fuzzy histon segmentation , 2013, Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine.
[5] Irene S. Karanasiou,et al. Glaucoma risk assessment using a non-linear multivariable regression method , 2012, Comput. Methods Programs Biomed..
[6] U. Rajendra Acharya,et al. Data mining technique for automated diagnosis of glaucoma using higher order spectra and wavelet energy features , 2012, Knowl. Based Syst..
[7] U. Acharya,et al. A survey and comparative study on the instruments for glaucoma detection. , 2012, Medical engineering & physics.
[8] U. Rajendra Acharya,et al. Algorithms for the Automated Detection of Diabetic Retinopathy Using Digital Fundus Images: A Review , 2012, Journal of Medical Systems.
[9] Chandan Chakraborty,et al. Application of higher order cumulants to ECG signals for the cardiac health diagnosis , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[10] U. Rajendra Acharya,et al. Automatic Detection of Epileptic EEG Signals Using Higher Order cumulant Features , 2011, Int. J. Neural Syst..
[11] U. Rajendra Acharya,et al. Automated Diagnosis of Glaucoma Using Texture and Higher Order Spectra Features , 2011, IEEE Transactions on Information Technology in Biomedicine.
[12] Chandan Chakraborty,et al. Quantitative Analysis of Sub-Epithelial Connective Tissue Cell Population of Oral Submucous Fibrosis Using Support Vector Machine , 2011 .
[13] U. Rajendra Acharya,et al. Analysis and Automatic Identification of Sleep Stages Using Higher Order Spectra , 2010, Int. J. Neural Syst..
[14] László G. Nyúl,et al. Glaucoma risk index: Automated glaucoma detection from color fundus images , 2010, Medical Image Anal..
[15] Hsin-Yi Chen,et al. Linear discriminant analysis and artificial neural network for glaucoma diagnosis using scanning laser polarimetry–variable cornea compensation measurements in Taiwan Chinese population , 2010, Graefe's Archive for Clinical and Experimental Ophthalmology.
[16] László G. Nyúl,et al. Retinal image analysis for automated glaucoma risk evaluation , 2009, International Symposium on Multispectral Image Processing and Pattern Recognition.
[17] U. Rajendra Acharya,et al. Automated Diagnosis of Glaucoma Using Digital Fundus Images , 2009, Journal of Medical Systems.
[18] C. M. Lim,et al. Computer-based detection of diabetes retinopathy stages using digital fundus images , 2009, Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine.
[19] Joel S Schuman,et al. Diagnostic tools for glaucoma detection and management. , 2008, Survey of ophthalmology.
[20] Mercedes Argüello Casteleiro,et al. Clinical practice guidelines: A case study of combining OWL-S, OWL, and SWRL , 2007, Knowl. Based Syst..
[21] László G. Nyúl,et al. Classifying Glaucoma with Image-Based Features from Fundus Photographs , 2007, DAGM-Symposium.
[22] Juan Xu,et al. Optic disk feature extraction via modified deformable model technique for glaucoma analysis , 2007, Pattern Recognit..
[23] Juan Xu,et al. Automated Optic Disk Boundary Detection by Modified Active Contour Model , 2007, IEEE Transactions on Biomedical Engineering.
[24] Qiaoping Zhang,et al. Accurate Centerline Detection and Line Width Estimation of Thick Lines Using the Radon Transform , 2007, IEEE Transactions on Image Processing.
[25] J. Olson,et al. Automatic detection of retinal anatomy to assist diabetic retinopathy screening , 2007, Physics in medicine and biology.
[26] Anders Heijl,et al. Trained Artificial Neural Network for Glaucoma Diagnosis Using Visual Field Data: A Comparison With Conventional Algorithms , 2007, Journal of glaucoma.
[27] Archie Sharma,et al. Automated depth analysis of optic nerve head from stereo fundus images , 2006 .
[28] Ronald R. Yager,et al. An extension of the naive Bayesian classifier , 2006, Inf. Sci..
[29] H. Quigley,et al. The number of people with glaucoma worldwide in 2010 and 2020 , 2006, British Journal of Ophthalmology.
[30] Mounir Mesbah,et al. Scoring of visual field measured through Humphrey perimetry: principal component varimax rotation followed by validated cluster analysis. , 2005, Investigative ophthalmology & visual science.
[31] Heinrich Niemann,et al. Automated segmentation of the optic nerve head for diagnosis of glaucoma , 2005, Medical Image Anal..
[32] E. Pifer,et al. Computer‐Aided Diagnosis , 2005 .
[33] Ming Li,et al. 2D-LDA: A statistical linear discriminant analysis for image matrix , 2005, Pattern Recognit. Lett..
[34] Enrico Grisan,et al. Detection of optic disc in retinal images by means of a geometrical model of vessel structure , 2004, IEEE Transactions on Medical Imaging.
[35] Thierry Blu,et al. Linear interpolation revitalized , 2004, IEEE Transactions on Image Processing.
[36] M. C. Leske,et al. Prevalence of open-angle glaucoma among adults in the United States. , 2004, Archives of ophthalmology.
[37] Michael H. Goldbaum,et al. Locating the optic nerve in a retinal image using the fuzzy convergence of the blood vessels , 2003, IEEE Transactions on Medical Imaging.
[38] Mauro Vavassori,et al. Detection of glaucomatous visual field changes using the Moorfields regression analysis of the Heidelberg retina tomograph. , 2003, American journal of ophthalmology.
[39] Stuart L. Graham,et al. Neural Network Model for Early Detection of Glaucoma using Multi-focal Visual Evoked Potential (M-VEP) , 2002 .
[40] Langis Gagnon,et al. Fast and robust optic disc detection using pyramidal decomposition and Hausdorff-based template matching , 2001, IEEE Transactions on Medical Imaging.
[41] Jiawei Han,et al. Data Mining: Concepts and Techniques , 2000 .
[42] A. Vingrys,et al. The many faces of glaucomatous optic neuropathy , 2000, Clinical & experimental optometry.
[43] H. Quigley. Number of people with glaucoma worldwide. , 1996, The British journal of ophthalmology.
[44] D. Geiger,et al. Learning Bayesian networks: The combination of knowledge and statistical data , 1994, Machine Learning.
[45] C. L. Nikias,et al. Signal processing with higher-order spectra , 1993, IEEE Signal Processing Magazine.
[46] A. Sommer,et al. Relationship between intraocular pressure and primary open angle glaucoma among white and black Americans. The Baltimore Eye Survey. , 1991, Archives of ophthalmology.
[47] Jerry M. Mendel,et al. Tutorial on higher-order statistics (spectra) in signal processing and system theory: theoretical results and some applications , 1991, Proc. IEEE.
[48] Keinosuke Fukunaga,et al. Introduction to statistical pattern recognition (2nd ed.) , 1990 .
[49] William M. Lyle. GLAUCOMA: A COLOUR MANUAL OF DIAGNOSIS AND TREATMENT , 1989 .
[50] R. Fisher. THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS , 1936 .
[51] U. Rajendra Acharya,et al. Wavelet-Based Energy Features for Glaucomatous Image Classification , 2012, IEEE Transactions on Information Technology in Biomedicine.
[52] Robert N Weinreb,et al. Clinical evaluation of the proper orthogonal decomposition framework for detecting glaucomatous changes in human subjects. , 2010, Investigative ophthalmology & visual science.
[53] G. Lavergne,et al. Biometric study of the disc cup in open-angle glaucoma , 2005, Graefe's Archive for Clinical and Experimental Ophthalmology.
[54] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[55] J. Radon. On the determination of functions from their integral values along certain manifolds , 1986, IEEE Transactions on Medical Imaging.
[56] Keinosuke Fukunaga,et al. Introduction to Statistical Pattern Recognition , 1972 .