Back-propagation Artificial Neural Network for Early Diabetic Retinopathy Detection Based On A Priori Knowledge

[1]  Gwénolé Quellec,et al.  Automated early detection of diabetic retinopathy. , 2010, Ophthalmology.

[2]  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.

[3]  M. Marcovecchio,et al.  Type 2 diabetes mellitus in children and adolescents , 2005, Journal of endocrinological investigation.

[4]  Jun Zhang,et al.  An automated computational framework for retinal vascular network labeling and branching order analysis. , 2012, Microvascular research.

[5]  K Nakamura,et al.  Effect of an artificial neural network on radiologists' performance in the differential diagnosis of interstitial lung disease using chest radiographs. , 1999, AJR. American journal of roentgenology.

[6]  Dong,et al.  Topological Framework Based Retinal Vessel Geometric Features Extraction and Selection with Least Absolute Shrinkage and Selection Operator , 2016 .

[7]  Chanjira Sinthanayothin,et al.  Automated screening system for diabetic retinopathy , 2003, 3rd International Symposium on Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the.

[8]  P Gain,et al.  Evaluation of automated fundus photograph analysis algorithms for detecting microaneurysms, haemorrhages and exudates, and of a computer-assisted diagnostic system for grading diabetic retinopathy. , 2010, Diabetes & metabolism.

[9]  F. E. A. El-Samie,et al.  Automated detection of diabetic retinopathy in blurred digital fundus images , 2012, 2012 8th International Computer Engineering Conference (ICENCO).

[10]  Wei Gao,et al.  Assessing the Performance of Optical Properties Determination of Intraretinal Layers in Healthy Normal and Type 1 Diabetic Eyes using Optical Coherence Tomography , 2011 .

[11]  U. Rajendra Acharya,et al.  Identification of different stages of diabetic retinopathy using retinal optical images , 2008, Inf. Sci..

[12]  T. Williamson,et al.  Automatic detection of diabetic retinopathy using an artificial neural network: a screening tool. , 1996, The British journal of ophthalmology.

[13]  Xiaofeng Zhang,et al.  Isotropic Undecimated Wavelet Transform Fuzzy Algorithm for Retinal Blood Vessel Segmentation , 2015 .

[14]  Shun-ichi Amari,et al.  Backpropagation and stochastic gradient descent method , 1993, Neurocomputing.

[15]  J. Anitha,et al.  An enhanced Counter Propagation Neural Network for abnormal retinal image classification , 2009, 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC).

[16]  J W Moul,et al.  Applications of neural networks in urologic oncology. , 1998, Seminars in urologic oncology.

[17]  Mehmet Celenk,et al.  Machine learning identification of diabetic retinopathy from fundus images , 2014, 2014 IEEE Signal Processing in Medicine and Biology Symposium (SPMB).

[18]  Rihard Karba,et al.  Incorporating prior knowledge into artificial neural networks - an industrial case study , 2004, Neurocomputing.

[19]  P. Lapuerta,et al.  Neural Network Assessment of Perioperative Cardiac Risk in Vascular Surgery Patients , 1998, Medical decision making : an international journal of the Society for Medical Decision Making.

[20]  Te-Won Lee,et al.  Bayesian machine learning classifiers for combining structural and functional measurements to classify healthy and glaucomatous eyes. , 2008, Investigative ophthalmology & visual science.

[21]  Davide Dazzi,et al.  Classification and prediction of the progression of thyroid-associated ophthalmopathy by an artificial neural network. , 2002, Ophthalmology.

[22]  R. Tibshirani.  Regression Shrinkage and Selection via the Lasso , 1996 .

[23]  P. Bankhead,et al.  Fast Retinal Vessel Detection and Measurement Using Wavelets and Edge Location Refinement , 2012, PloS one.

[24]  Marco Muselli,et al.  Differential diagnosis of pleural mesothelioma using Logic Learning Machine , 2015, BMC Bioinformatics.

[25]  T. Reinehr,et al.  Type 2 diabetes mellitus in children and adolescents. , 2013, World journal of diabetes.

[26]  Ali Elkamel,et al.  Modeling of complex dynamic systems using differential neural networks with the incorporation of a priori knowledge , 2015, Appl. Math. Comput..

[27]  J. Shaw,et al.  Global estimates of the prevalence of diabetes for 2010 and 2030. , 2010, Diabetes research and clinical practice.

[28]  Hyunsoo Yoon,et al.  Algorithm learning based neural network integrating feature selection and classification , 2013, Expert Syst. Appl..

[29]  Mahua Nandy,et al.  Retinal vessel segmentation using Gabor filter and artificial neural network , 2012, 2012 Third International Conference on Emerging Applications of Information Technology.

[30]  George G. Lendaris,et al.  Improving ANN generalization using a priori knowledge to pre-structure ANNs , 1997, Proceedings of International Conference on Neural Networks (ICNN'97).