Local configuration pattern features for age-related macular degeneration characterization and classification
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Kevin Noronha | U. Rajendra Acharya | Sulatha V. Bhandary | Hamido Fujita | Chua Kuang Chua | Choo Min Lim | Joel E. W. Koh | Augustinus Laude | Jen Hong Tan | Louis Tong | Muthu Rama Krishnan Mookiah | C. M. Lim | Joel E. W. Koh | C. K. Chua | J. Tan | U. Acharya | S. Bhandary | H. Fujita | A. Laude | L. Tong | K. Noronha | M. Mookiah
[1] David A. Landgrebe,et al. A survey of decision tree classifier methodology , 1991, IEEE Trans. Syst. Man Cybern..
[2] AcharyaU. Rajendra,et al. Computer-aided diagnosis of diabetic retinopathy , 2013 .
[3] U. Rajendra Acharya,et al. Computer-aided diagnosis of diabetic retinopathy: A review , 2013, Comput. Biol. Medicine.
[4] Oliver Faust,et al. AUTOMATED GLAUCOMA DETECTION USING HYBRID FEATURE EXTRACTION IN RETINAL FUNDUS IMAGES , 2013 .
[5] Jin Tae Kwak,et al. Efficient data mining for local binary pattern in texture image analysis , 2015, Expert Syst. Appl..
[6] U. Rajendra Acharya,et al. Ensemble selection for feature-based classification of diabetic maculopathy images , 2013, Comput. Biol. Medicine.
[7] Karel J. Zuiderveld,et al. Contrast Limited Adaptive Histogram Equalization , 1994, Graphics Gems.
[8] Frank Eperjesi,et al. Use of fundus imaging in quantification of age-related macular change. , 2007, Survey of ophthalmology.
[9] Philippe Burlina,et al. Automated detection of drusen in the macula , 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.
[10] G. Coscas,et al. A new approach of geodesic reconstruction for drusen segmentation in eye fundus images , 2001, IEEE Transactions on Medical Imaging.
[11] Matti Pietikäinen,et al. Texture Classification using a Linear Configuration Model based Descriptor , 2011, BMVC.
[12] Uğur Şevik,et al. Automatic segmentation of age-related macular degeneration in retinal fundus images , 2008, Comput. Biol. Medicine.
[13] U. Rajendra Acharya,et al. Evolutionary algorithm based classifier parameter tuning for automatic diabetic retinopathy grading: A hybrid feature extraction approach , 2013, Knowl. Based Syst..
[14] Alex C. Michalos,et al. Fundamentals of Statistics. Vol. I. , 1969 .
[15] Bálint Antal,et al. An Ensemble-Based System for Microaneurysm Detection and Diabetic Retinopathy Grading , 2012, IEEE Transactions on Biomedical Engineering.
[16] Kevin Noronha,et al. Automated diagnosis of Age-related Macular Degeneration using greyscale features from digital fundus images , 2014, Comput. Biol. Medicine.
[17] Frans Coenen,et al. Retinal image classification using a histogram based approach , 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).
[18] Ayyakkannu Manivannan,et al. Automated drusen detection in retinal images using analytical modelling algorithms , 2011, Biomedical engineering online.
[19] Adam W. Hoover,et al. Drusen Detection in a Retinal Image Using Multi-level Analysis , 2003, MICCAI.
[20] László G. Nyúl,et al. Glaucoma risk index: Automated glaucoma detection from color fundus images , 2010, Medical Image Anal..
[21] Li Guo,et al. Imaging in DRY AMD , 2013 .
[22] Baihua Li,et al. Automatic extraction of retinal features from colour retinal images for glaucoma diagnosis: A review , 2013, Comput. Medical Imaging Graph..
[23] Ching Y. Suen,et al. Application of majority voting to pattern recognition: an analysis of its behavior and performance , 1997, IEEE Trans. Syst. Man Cybern. Part A.
[24] Frans Coenen,et al. Automated "disease/no disease" grading of age-related macular degeneration by an image mining approach. , 2012, Investigative ophthalmology & visual science.
[25] John D. Austin,et al. Adaptive histogram equalization and its variations , 1987 .
[26] José Francisco Martínez Trinidad,et al. Mining patterns for clustering on numerical datasets using unsupervised decision trees , 2015, Knowl. Based Syst..
[27] P. Soliz,et al. Independent Component Analysis for Vision-inspired Classification of Retinal Images with Age-related Macular Degeneration , 2008, 2008 IEEE Southwest Symposium on Image Analysis and Interpretation.
[28] Victor Murray,et al. Automatic detection of diabetic retinopathy and age-related macular degeneration in digital fundus images. , 2011, Investigative ophthalmology & visual science.
[29] A. Bhuiyan,et al. A Review of Disease Grading and Remote Diagnosis for Sight Threatening Eye Condition: Age Related Macular Degeneration , 2014 .
[30] LamL.,et al. Application of majority voting to pattern recognition , 1997 .
[31] Donald F. Specht,et al. Probabilistic neural networks , 1990, Neural Networks.
[32] R. Klein,et al. Global prevalence of age-related macular degeneration and disease burden projection for 2020 and 2040: a systematic review and meta-analysis. , 2014, The Lancet. Global health.
[33] Ron Kohavi,et al. A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection , 1995, IJCAI.
[34] B. van Ginneken,et al. Automated detection and differentiation of drusen, exudates, and cotton-wool spots in digital color fundus photographs for diabetic retinopathy diagnosis. , 2007, Investigative ophthalmology & visual science.
[35] Cemal Köse,et al. A Statistical Segmentation Method for Measuring Age-Related Macular Degeneration in Retinal Fundus Images , 2010, Journal of Medical Systems.
[36] Chandan Chakraborty,et al. Small retinal vessels extraction towards proliferative diabetic retinopathy screening , 2012, Expert Syst. Appl..
[37] Gwénolé Quellec,et al. Optimal Filter Framework for Automated, Instantaneous Detection of Lesions in Retinal Images , 2011, IEEE Transactions on Medical Imaging.
[38] P.T.V.M. de Jong,et al. Mechanisms of disease: Age-related macular degeneration , 2006 .
[39] Jennifer R. Evans,et al. Risk Factors for Age-related Macular Degeneration , 2001, Progress in Retinal and Eye Research.
[40] Francisco Herrera,et al. A survey of fingerprint classification Part II , 2015 .
[41] S T Roweis,et al. Nonlinear dimensionality reduction by locally linear embedding. , 2000, Science.
[42] Jennifer I. Lim,et al. A randomized, placebo-controlled, clinical trial of high-dose supplementation with vitamins C and E, beta carotene, and zinc for age-related macular degeneration and vision loss: AREDS report no. 8. , 2001, Archives of ophthalmology.
[43] Philippe Burlina,et al. Automatic screening of age-related macular degeneration and retinal abnormalities , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[44] Tommy W. S. Chow,et al. Automatic image annotation via compact graph based semi-supervised learning , 2015, Knowl. Based Syst..
[45] Tien Yin Wong,et al. Early age-related macular degeneration detection by focal biologically inspired feature , 2012, 2012 19th IEEE International Conference on Image Processing.
[46] Marios S. Pattichis,et al. Multi-scale AM-FM for lesion phenotyping on age-related macular degeneration , 2009, 2009 22nd IEEE International Symposium on Computer-Based Medical Systems.
[47] David G. Stork,et al. Pattern Classification , 1973 .
[48] H. Santos-Villalobos,et al. Statistical characterization and segmentation of drusen in fundus images , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[49] Hishammuddin Asmuni,et al. A low lighting or contrast ratio visible iris recognition using iso-contrast limited adaptive histogram equalization , 2015, Knowl. Based Syst..
[50] Divya Tomar,et al. A comparison on multi-class classification methods based on least squares twin support vector machine , 2015, Knowl. Based Syst..
[51] Michalis E. Zervakis,et al. Detection and segmentation of drusen deposits on human retina: Potential in the diagnosis of age-related macular degeneration , 2003, Medical Image Anal..
[52] Linda Pring. Blindness and visual disability , 2007 .
[53] D. Verma,et al. Age related macular degeneration: Authors' reply , 2003, BMJ : British Medical Journal.
[54] Frans Coenen,et al. Data Mining for AMD Screening: A Classification Based Approach , 2020 .
[55] Frans Coenen,et al. Data mining techniques for the screening of age-related macular degeneration , 2012, Knowl. Based Syst..
[56] Guoli Ji,et al. PLS-based recursive feature elimination for high-dimensional small sample , 2014, Knowl. Based Syst..
[57] Matti Pietikäinen,et al. Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns , 2002, IEEE Trans. Pattern Anal. Mach. Intell..
[58] Kevin Noronha,et al. Decision support system for age-related macular degeneration using discrete wavelet transform , 2014, Medical & Biological Engineering & Computing.
[59] K. Chan,et al. Towards automatic detection of age-related macular degeneration in retinal fundus images , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.
[60] Parul Ichhpujani,et al. DIAGNOSTIC AND SURGICAL TECHNIQUES , 2005 .