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Neural Networks with Manifold Learning for Diabetic Retinopathy Detection [article]

Arjun Raj Rajanna, Kamelia Aryafar, Rajeev Ramchandran, Christye Sisson, Ali Shokoufandeh, Raymond Ptucha
2016 arXiv   pre-print
In this paper, we introduce a set of neural networks for diabetic retinopathy classification of fundus retinal images.  ...  Moreover the proposed models are scalable and can be used in large scale datasets for diabetic retinopathy detection.  ...  for diabetic retinopathy detection.  ... 
arXiv:1612.03961v1 fatcat:3qk65gbz6bh4lp37a642h67z6i

Diabetic Retinopathy Detection Using Neural Network

Finding of diabetic retinopathy in fundus imaginary is done by computer vision and deep learning methods using artificial neural networks.  ...  The images of the diabetic retinopathy datasets are trained in neural networks.  ...  Diabetic Retinopathy Detection Using Neural Network Convolutional Neural Networks (CNNs), a division of deep learning, consume an imposing record aimed at requests vogueish image examination and clarification  ... 
doi:10.35940/ijitee.j1105.0881019 fatcat:fqq5ovg4uzfklexmt4ppcy7wey

Fundus Image Classification Using VGG-19 Architecture with PCA and SVD

Muhammad Mateen, Junhao Wen, Nasrullah, Sun Song, Zhouping Huang
2018 Symmetry  
Deep neural network (DNN) is widely used to classify diabetic retinopathy from fundus images collected from suspected persons.  ...  Diabetic retinopathy (DR) is a retinal disease that is diagnosed in diabetic patients.  ...  [8] promoted DCNN for diabetic retinopathy detection. Gulshan et al.  ... 
doi:10.3390/sym11010001 fatcat:5whoki33a5ajvmvueafrp5atdu

An Effective Screening System to Detect Diabetic Retinopathy by using Dehazing Technique

2020 International journal of recent technology and engineering  
The Diabetic Retinopathy (DR) is playing a crucial role in clinical data analysis to diagnose abnormality in retina.  ...  The abnormality in the blood vessels of diabetics, a way will be paved for prompt diagnosis of DR.  ...  Block diagram of diabetic retinopathy detection system.  ... 
doi:10.35940/ijrte.d4297.018520 fatcat:ssxh5r3s4bhirjto6oqxzl2rxi

Identification of Diabetic Retinopathy through Machine Learning

Malik Bader Alazzam, Fawaz Alassery, Ahmed Almulihi, Hasan Ali Khattak
2021 Mobile Information Systems  
In particular, the RBM model of machine learning automatic disease detection performed well in terms of diagnostic accuracy, sensitivity, and application in diabetic retinopathy screening.  ...  A cross-sectional study of patients with suspected diabetic retinopathy (DR) who had an ophthalmological examination and a retinal scan is the focus of this research.  ...  Acknowledgments e authors deeply acknowledge Taif University, Saudi Arabia, for supporting this study through Taif University Researchers Supporting Project number TURSP-2020/344.  ... 
doi:10.1155/2021/1155116 fatcat:spzlhy4tmjff7nlwirwn5wpi34

Artificial intelligence and deep learning in ophthalmology

Daniel Shu Wei Ting, Louis R Pasquale, Lily Peng, John Peter Campbell, Aaron Y Lee, Rajiv Raman, Gavin Siew Wei Tan, Leopold Schmetterer, Pearse A Keane, Tien Yin Wong
2018 British Journal of Ophthalmology  
In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography and visual fields, achieving robust classification performance in the detection of diabetic retinopathy and retinopathy  ...  DL in ocular imaging may be used in conjunction with telemedicine as a possible solution to screen, diagnose and monitor major eye diseases for patients in primary care and community settings.  ...  dL AppLICATIons In ophThALmoLogy diabetic retinopathy Globally, 600 million people will have diabetes by 2040, with a third having DR. 22 A pooled analysis of 22 896 people with diabetes from 35 population-based  ... 
doi:10.1136/bjophthalmol-2018-313173 pmid:30361278 pmcid:PMC6362807 fatcat:xggqvj4bevegfdrjvdap6ibp3m

Diabetic Retinopathy Detection Using VGG-NIN a Deep Learning Architecture

Zubair Khan, Fiaz Gul Khana, Ahmad Khan, Zia ur Rehman, Sajid Shah, Sehrish Qummar, Farman Ali, Sangheon Pack
2021 IEEE Access  
CONCLUSION This paper is an extension of our work [9] in which we proposed the deep learning-based ensemble approach for diabetic retinopathy detection.  ...  [15] proposed a CNN Referable Diabetic Retinopathy (RDR). They evaluated the network performance on two different data sets for binary classification.  ... 
doi:10.1109/access.2021.3074422 fatcat:dzdbbbqqbrcqnb3pjhp526u3vi

DR-LL Gan: Diabetic Retinopathy Lesions Synthesis using Generative Adversarial Network

Saif Hameed Abbood, Haza Nuzly Abdull Hamed, Mohd Shafry Mohd Rahim, Abdul Hadi M. Alaidi, Haider Th.Salim Alrikabi
2022 International Journal of Online and Biomedical Engineering (iJOE)  
Deep learning techniques typically need huge picture data sets for deep convolutional neural networks (DCNNs) training, it should be graded by human specialists.  ...  Deep learning (DL) techniques are commonly used utilized in ophthalmology for discriminative tasks such as diabetic retinopathy or age-related macular degeneration (AMD) diagnosis.  ...  Clinically effective DL approaches have been built for a number of applications in ophthalmology, including the detection of several eye disorders such as diabetic retinopathy (DR) [1, [5] [6] [7] [8]  ... 
doi:10.3991/ijoe.v18i03.28005 fatcat:xglsrg2iqvco7o4hvp6iunx5ja

Leveraging Deep Learning for Designing Healthcare Analytics Heuristic for Diagnostics

Sarah Shafqat, Maryyam Fayyaz, Hasan Ali Khattak, Muhammad Bilal, Shahid Khan, Osama Ishtiaq, Almas Abbasi, Farzana Shafqat, Waleed S. Alnumay, Pushpita Chatterjee
2021 Neural Processing Letters  
For this task researchers are doing explorations in big data analytics, deep learning (advanced form of machine learning known as deep neural nets), predictive analytics and various other algorithms to  ...  In this paper, Louvain Mani-Hierarchical Fold Learning healthcare analytics, a hybrid deep learning technique is proposed for medical diagnostics and is tested and validated using real-time dataset of  ...  The data contributed for diagnosis of Dengue Fever ( Fig. 5 and 6) , infectious diseases having Covid-19 (Fig. 8) or Diabetes and its comorbidities (as in Fig. 11 , 13 and 14) holds a lot of worth  ... 
doi:10.1007/s11063-021-10425-w pmid:33551665 pmcid:PMC7852051 fatcat:nfs3pi5ed5b6vjzjfcz6odm4vm

Adversarial Attack and Defence through Adversarial Training and Feature Fusion for Diabetic Retinopathy Recognition

Sheeba Lal, Saeed Ur Rehman, Jamal Hussain Shah, Talha Meraj, Hafiz Tayyab Rauf, Robertas Damaševičius, Mazin Abed Mohammed, Karrar Hameed Abdulkareem
2021 Sensors  
We evaluate and analyze the adversarial attacks and defenses on the retinal fundus images for the Diabetic Retinopathy recognition problem, which is considered a state-of-the-art endeavor.  ...  Practical application in actual physical scenarios with adversarial threats shows their features.  ...  the detection of diabetic retinopathy (DR) by using the Eyepacs Dataset with high-quality images and transferal rates.  ... 
doi:10.3390/s21113922 fatcat:ctlmaxj45bfdllzxclu7utc5we

2020 Index IEEE Journal of Biomedical and Health Informatics Vol. 24

2020 IEEE journal of biomedical and health informatics  
., A Globalized Model for Mapping Wearable Seismocardiogram Signals to Whole-Body Ballistocardiogram Signals Based on Deep Learning; JBHI May 2020 1296-1309 Herskovic, V., see Saint-Pierre, C., JBHI Jan  ...  ., +, JBHI Oct. 2020 3020-3028 A Deep Neural Network Application for Improved Prediction of HbA 1c in Type 1 Diabetes.  ...  ., +, JBHI Oct. 2020 2755-2764 A Deep Neural Network Application for Improved Prediction of HbA 1c in Type 1 Diabetes.  ... 
doi:10.1109/jbhi.2020.3048808 fatcat:iifrkwtzazdmboabdqii7x5ukm

A Tetrahedron-Based Heat Flux Signature for Cortical Thickness Morphometry Analysis [chapter]

Yonghui Fan, Gang Wang, Natasha Lepore, Yalin Wang
2018 Lecture Notes in Computer Science  
for Identifying Diabetic Retinopathy Based on Anti-noise Detection and Attention-based Fusion 458 Magnetic Resonance Spectroscopy Quantification using Deep Learning 460 DeepHCS: Bright-field to Fluorescence  ...  314 Densely Deep Supervised Networks with Threshold Loss for Cancer Detection in Automated Breast Ultrasound 316 SPNet: Shape Prediction using a Fully Convolutional Neural Network 317 Modeling Longitudinal  ... 
doi:10.1007/978-3-030-00931-1_48 pmid:30338317 pmcid:PMC6191198 fatcat:dqhvpm5xzrdqhglrfftig3qejq

Analysis of Dimensionality Reduction Techniques on Big Data

Thippa Reddy G, Praveen Kumar Reddy M, Kuruva Lakshmanna, Rajesh Kaluri, Dharmendra Singh Rajput, Gautam Srivastava, Thar Baker
2020 IEEE Access  
Retinopathy (DR) and Intrusion Detection System (IDS) datasets.  ...  Not all the attributes in the datasets generated are important for training the machine learning algorithms.  ...  The authors in [37] present a PCA-Firefly based Deep Learning Model for early detection of diabetic retinopathy.  ... 
doi:10.1109/access.2020.2980942 fatcat:x3aywvxjenccfitimfxxk5i7ea

Exploring Adversarial Examples: Patterns of One-Pixel Attacks [article]

David Kügler, Alexander Distergoft, Arjan Kuijper, Anirban Mukhopadhyay
2018 arXiv   pre-print
We hypothesize that adversarial examples might result from the incorrect mapping of image space to the low dimensional generation manifold by deep networks.  ...  Failure cases of black-box deep learning, e.g. adversarial examples, might have severe consequences in healthcare.  ...  In the United States, the FDA has embraced this change by approving AI devices for diabetic retinopathy detection [1] and is currently in the discussion towards easing the approval process for AI-based  ... 
arXiv:1806.09410v1 fatcat:mtcfm2rtovh4lkbo6eawfjn674

Benchmarking Differentially Private Residual Networks for Medical Imagery [article]

Sahib Singh, Harshvardhan Sikka, Sasikanth Kotti, Andrew Trask
2020 arXiv   pre-print
These retinal images can help identify diabetic retinopathy automatically. Diabetic retinopathy (DR) refers to a diabetes complication affecting eyes.  ...  Figure 1 . 1 Examples from the APTOS Blindness Detection Dataset. Samples progress in severity of Diabetic Retinopathy.  ... 
arXiv:2005.13099v5 fatcat:hy4jqdq235befebroyvju3yyru
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