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Classification of Diabetic Retinopathy using Stacked Autoencoder-Based Deep Neural Network

Yasir Eltigani Ali Mustaf, Department of Information Systems, Ahmed Bin Mohamed Military College, Doha, Qatar., Bashir Hassan Ismail, Breaking Barriers, United Kingdom.
2020 Journal of Computational Science and Intelligent Technologies  
Diagnosis of diabetic retinopathy (DR) via images of colour fundus requires experienced clinicians to determine the presence and importance of a large number of small characteristics.  ...  This work proposes and named Adapted Stacked Auto Encoder (ASAE-DNN) a novel deep learning framework for diabetic retinopathy (DR), three hidden layers have been used to extract features and classify them  ...  ACKNOWLEDGEMENTS The authors would like to thank their present employer for providing support while carrying out this research work.  ... 
doi:10.53409/mnaa.jcsit1102 fatcat:kqrfbop2ijer7de5npsvkxwsea

Application of Deep Learning in Fundus Image Processing for Ophthalmic Diagnosis – A Review [article]

Sourya Sengupta, Amitojdeep Singh, Henry A.Leopold, Tanmay Gulati, Vasudevan Lakshminarayanan
2019 arXiv   pre-print
An overview of the applications of deep learning in ophthalmic diagnosis using retinal fundus images is presented.  ...  We also review various retinal image datasets that can be used for deep learning purposes.  ...  A previously trained model with ImageNet database was used and the output layer was replaced by a new output layer with 2 nodes for 2 different classes-normal and glaucoma.  ... 
arXiv:1812.07101v3 fatcat:weoh4wnw4ngy5mmq7vwgr2p77e

Beyond Retinal Layers: A Deep Voting Model for Automated Geographic Atrophy Segmentation in SD-OCT Images

Zexuan Ji, Qiang Chen, Sijie Niu, Theodore Leng, Daniel L. Rubin
2018 Translational Vision Science & Technology  
Results: Two image data sets with GA were used to evaluate the model.  ...  During the training phase, the labeled A-scans with 1024 features were directly fed into the network as the input layer to obtain the deep representations.  ...  As a noninvasive imaging technique for the ocular fundus, FAF can provide two-dimensional (2D) images with high contrast for the identification of GA.  ... 
doi:10.1167/tvst.7.1.1 pmid:29302382 pmcid:PMC5749649 fatcat:h3zc6n4v7rhfxdrdhlktmun3de

Deep Learning and Medical Diagnosis: A Review of Literature

Mihalj Bakator, Dragica Radosav
2018 Multimodal Technologies and Interaction  
In this review the application of deep learning for medical diagnosis is addressed.  ...  A thorough analysis of various scientific articles in the domain of deep neural networks application in the medical field has been conducted.  ...  [20] CNN Fundus images Glaucoma detection; the experiments were performed on SCES and ORIGA datasets; further, it was noted that this approach may be great for glaucoma detection.  ... 
doi:10.3390/mti2030047 fatcat:c6ulsgl3kndszedl7ewil6lotu

Retinal Vessels Segmentation Techniques and Algorithms: A Survey

Jasem Almotiri, Khaled Elleithy, Abdelrahman Elleithy
2018 Applied Sciences  
Firstly, a brief introduction to retinal fundus photography and imaging modalities of retinal images is given.  ...  With the development of almost two decades, the innovative approaches applying computer-aided techniques for segmenting retinal vessels are becoming more and more crucial and coming closer to routine clinical  ...  Then, the retinal image was divided into two major layers: texture layer and smooth layer.  ... 
doi:10.3390/app8020155 fatcat:ohixrrcbwrdj3hcdgnib3ne2o4

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  ...  , Ballistocardiography Can Estimate Beat-to-Beat Heart Rate Accurately at Night in Patients After Vascular Intervention; JBHI Aug. 2020 2230-2237 Hoogi, A., Mishra, A., Gimenez, F., Dong, J., and Rubin  ...  ., +, TSE-CNN: A Two-Stage End-to-End CNN for Human Activity Recognition. Huang, J., +, JBHI Jan. 2020 292-299 Unsupervised 3D End-to-End Medical Image Registration With Volume Tweening Network.  ... 
doi:10.1109/jbhi.2020.3048808 fatcat:iifrkwtzazdmboabdqii7x5ukm

Conditional Generative Adversarial Networks for Metal Artifact Reduction in CT Images of the Ear [chapter]

Jianing Wang, Yiyuan Zhao, Jack H. Noble, Benoit M. Dawant
2018 Lecture Notes in Computer Science  
to Retinal Diseases Yitian Zhao*; Yalin Zheng; Yifan Zhao; Yonghuai Liu; Zhili Chen; Peng Liu; Jiang Liu M-115 Towards a Glaucoma Risk Index Based on Simulated Hemodynamics from Fundus Images Deep Supervision  ...  Aortic Image Sequence Segmentation with Sparse Annotations Wenjia Bai*; Hideaki Suzuki; Chen Qin; Giacomo Tarroni; Ozan Oktay; Paul M.  ... 
doi:10.1007/978-3-030-00928-1_1 fatcat:ypoj3zplm5awljf6u5c2spgiea

Artificial Intelligence Algorithms for Analysis of Geographic Atrophy: A Review and Evaluation

Janan Arslan, Gihan Samarasinghe, Kurt K. Benke, Arcot Sowmya, Zhichao Wu, Robyn H. Guymer, Paul N. Baird
2020 Translational Vision Science & Technology  
The search strategy and selection of publications were both conducted in accordance with the Preferred of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.  ...  However, there is a need for the development of reliable and objective models and software to predict the rate of GA progression and to quantify improvements due to interventions.  ...  al., 2018 a, b37 IR 70 images from 70 subjects CNN Yes Ji et al., 2018 38 SD-OCT Dataset 1: 51 scans Dataset 2: 54 scans Sparse autoencoders deep network Yes Xu et al., 2018 b39  ... 
doi:10.1167/tvst.9.2.57 pmid:33173613 pmcid:PMC7594588 fatcat:qaoroqvjnrdg5gvz4ozzjmq2ai

Data Analysis Methods for Software Systems

Jolita Bernatavičienė
2021 Vilnius University Proceedings  
But this conference is not a hybrid conference, as the main objective is live interaction between researchers. History of the conference starts from 2009 with 16 presentations.  ...  This means that the topics of the conference are actual for business, too.  ...  Various eye diseases such as glaucoma, diabetic retinopathy and hypertension can be diagnosed using eye fundus images. Therefore, image analysis is necessary.  ... 
doi:10.15388/damss.12.2021 fatcat:iefv6bz3drcrfpcwxoaqmu3gra

Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future

David Ahmedt-Aristizabal, Mohammad Ali Armin, Simon Denman, Clinton Fookes, Lars Petersson
2021 Sensors  
With the advances of data-driven machine learning research, a wide variety of prediction problems have been tackled.  ...  We also outline the limitations of existing techniques and discuss potential directions for future research.  ...  Optic disc/cup and fetal head: The size of the optic disc and optic cup in color fundus images is also of great importance for the diagnosis of glaucoma, an irreversible eye disease. Meng et al.  ... 
doi:10.3390/s21144758 fatcat:jytyt4u2pjgvhnhcto3vcvd3a4

Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future [article]

David Ahmedt-Aristizabal, Mohammad Ali Armin, Simon Denman, Clinton Fookes, Lars Petersson
2021 arXiv   pre-print
With the advances of data-driven machine learning research, a wide variety of prediction problems have been tackled.  ...  We also outline the limitations of existing techniques and discuss potential directions for future research.  ...  This framework is illustrated in Fig. 22 . d) Optic disc/cup and fetal head: The size of the optic disc and optic cup in color fundus images is also of great importance for the diagnosis of glaucoma,  ... 
arXiv:2105.13137v1 fatcat:gm7d2ziagba7bj3g34u4t3k43y

Learning Neural Textual Representations for Citation Recommendation

Binh Thanh Kieu, Inigo Jauregi Unanue, Son Bao Pham, Hieu Xuan Phan, Massimo Piccardi
2021 2020 25th International Conference on Pattern Recognition (ICPR)  
Image-Based Person Re-Identification DAY 2 -Jan 13, 2021 Liu, Xiyao; Ma, Ziping; Guo, Xingbei; Hou, Jialu; Wang, Lei; Schaefer, Gerald; Fang, Hui 2129 Joint Compressive Autoencoders for Full-Image-To-Image  ...  Deep Neural Networks Using Knowledge Distillation DAY 2 -Jan 13, 2021 Kanno, Yuri; Yasuda, Muneki 2108 Multi-Layered Discriminative Restricted Boltzmann Machine with Untrained Probabilistic Layer  ... 
doi:10.1109/icpr48806.2021.9412725 fatcat:3vge2tpd2zf7jcv5btcixnaikm

A retinal vasculature tracking system guided by a deep architecture

Fatmatülzehra Uslu, Anil Anthony Bharath, Turkey. Ministry Of National Education
2019
Analysing the vasculature in fundus images may provide a tool for ophthalmologists to diagnose eye-related diseases and to monitor their progression.  ...  Although segmentation can provide vasculature existence in a fundus image, it does not give quantifiable measures for vasculature. The latter has more practical value in medical clinics.  ...  Input Layer Hidden Layer h j W ij (a) (b) RBMs RBMs A Traditional RBM vs A Traditional Autoencoder Similar to traditional autoencoders, traditional RBMs have two layers.  ... 
doi:10.25560/75502 fatcat:6oig2khoinawrb7xlghfr7bqp4

Natural Language Processing and Information Extraction

Νικόλαος Ε. Στυλιανού
2021
First, we present a series of novel architectures for refined Biomedical Entity Recognition, with specific focus in Evidence-Based Medicine entities.  ...  Capitalizing on the importance of semantic entities, we present two methodologies to incorporate coreferent information in Language Modeling.  ...  We implemented two BiLSTMs, with a Highway Residual connection between, with hidden sizes of each LSTM layers, drnn , 712 for the first and 365 for the second.  ... 
doi:10.26262/heal.auth.ir.334427 fatcat:xnmddj3t7jg7poadfwrsxqsi6a