Identification of Diabetic Retinopathy for Retinal Images Using Feed Forward Neural Network

[1]  Luc Van Gool,et al.  Deep Retinal Image Understanding , 2016, MICCAI.

[2]  Darvin Yi,et al.  Automated Detection of Diabetic Retinopathy using Deep Learning , 2018, AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science.

[3]  Boreom Lee,et al.  Development of automatic retinal vessel segmentation method in fundus images via convolutional neural networks , 2017, 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[4]  Joachim M. Buhmann,et al.  Glaucoma detection using entropy sampling and ensemble learning for automatic optic cup and disc segmentation , 2017, Comput. Medical Imaging Graph..

[5]  Krzysztof Krawiec,et al.  Segmenting Retinal Blood Vessels With Deep Neural Networks , 2016, IEEE Transactions on Medical Imaging.

[6]  Ganesh Naik,et al.  A supervised blood vessel segmentation technique for digital Fundus images using Zernike Moment based features , 2020, PloS one.

[7]  S. Edward Rajan,et al.  Computerized screening of diabetic retinopathy employing blood vessel segmentation in retinal images , 2014 .

[8]  Ayman El-Baz,et al.  Automatic blood vessels segmentation based on different retinal maps from OCTA scans , 2017, Comput. Biol. Medicine.

[9]  José Manuel Bravo,et al.  A New Supervised Method for Blood Vessel Segmentation in Retinal Images by Using Gray-Level and Moment Invariants-Based Features , 2011, IEEE Transactions on Medical Imaging.

[10]  Kimmo Kaski,et al.  Deep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Grading , 2019, Scientific Reports.

[11]  Alireza Mehridehnavi,et al.  Macular OCT Classification Using a Multi-Scale Convolutional Neural Network Ensemble , 2018, IEEE Transactions on Medical Imaging.

[12]  A. M. R. R. Bandara,et al.  A retinal image enhancement technique for blood vessel segmentation algorithm , 2017, 2017 IEEE International Conference on Industrial and Information Systems (ICIIS).

[13]  Inas A. Yassine,et al.  Convolutional neural networks for deep feature learning in retinal vessel segmentation , 2016, 2016 IEEE International Conference on Image Processing (ICIP).

[14]  Vivekanandan Periyasamy,et al.  Retinal vessel segmentation using neural network , 2018, IET Image Process..

[15]  Chunlan Yang,et al.  Automatic parameters selection of Gabor filters with the imperialism competitive algorithm with application to retinal vessel segmentation , 2017 .

[16]  Amol Prataprao Bhatkar,et al.  Detection of Diabetic Retinopathy in Retinal Images Using MLP Classifier , 2015, 2015 IEEE International Symposium on Nanoelectronic and Information Systems.

[17]  Bunyarit Uyyanonvara,et al.  Automatic detection of diabetic retinopathy exudates from non-dilated retinal images using mathematical morphology methods , 2008, Comput. Medical Imaging Graph..

[18]  Santi P. Maity,et al.  Retinal blood vessel segmentation using matched filter and Laplacian of Gaussian , 2016, 2016 International Conference on Signal Processing and Communications (SPCOM).

[19]  Jaskirat Kaur,et al.  A generalized method for the segmentation of exudates from pathological retinal fundus images , 2018 .

[20]  Charles V. Stewart,et al.  Retinal Vessel Centerline Extraction Using Multiscale Matched Filters, Confidence and Edge Measures , 2006, IEEE Transactions on Medical Imaging.

[21]  Jianqiang Li,et al.  Comparative Analysis of Vessel Segmentation Techniques in Retinal Images , 2019, IEEE Access.

[22]  Meng Li,et al.  Robust Retinal Blood Vessel Segmentation Based on Reinforcement Local Descriptions , 2017, BioMed research international.