Article
Computer Science, Information Systems
Thayanee Ruennak, Pakinee Aimmanee, Stanislav Makhanov, Navapol Kanchanaranya, Sakchai Vongkittirux
Summary: The study aims to verify the feasibility of integrating a handheld camera with fast computational methods into a mobile phone, proposing an effective solution named DES for segmenting abnormalities in mobile phone fundus images and detecting diabetic retinopathy.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Computer Science, Information Systems
German Pinedo-Diaz, Susana Ortega-Cisneros, Eduardo Ulises Moya-Sanchez, Jorge Rivera, Pedro Mejia-Alvarez, Francisco J. Rodriguez-Navarrete, Abraham Sanchez
Summary: Diabetic retinopathy is a major cause of blindness, and automated diabetes screening plays a crucial role in identifying lesions and reducing the risk of blindness. This study proposes a deep learning-based algorithm that analyzes spatial domain features and image quality assessment metrics to perform efficient diabetes screening and detect significant features with low computational cost, achieving high sensitivity and specificity.
Article
Robotics
Avleen Malhi, Reaya Grewal, Husanbir Singh Pannu
Summary: Diabetic Retinopathy is an eye disorder caused by high blood sugar levels in diabetes patients, which damages blood vessels in the eyes and can lead to blindness. This paper proposes a simple and effective technique for early detection of exudates and microaneurysms, which can save the patient's vision. The research uses image processing, features extraction, and machine learning to accurately predict the presence of exudates and microaneurysms and grade the severity of the disease.
INTERNATIONAL JOURNAL OF INTELLIGENT ROBOTICS AND APPLICATIONS
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
N. Jagan Mohan, R. Murugan, Tripti Goel, Parthapratim Roy
Summary: Diabetic retinopathy is a common and serious health condition that affects the retinal blood vessels and can lead to vision loss. In this paper, a novel method based on modified KAZE features and ELMAE is proposed to accurately localize exudates in fundus images. The experimental results show that the proposed method achieves high sensitivity, specificity, and accuracy, with a short processing time.
JOURNAL OF DIGITAL IMAGING
(2022)
Article
Anatomy & Morphology
Malik Abdul Manan, Feng Jinchao, Tariq M. M. Khan, Muhammad Yaqub, Shahzad Ahmed, Imran Shabir Chuhan
Summary: This study proposes a deep convolutional neural network (CNN) architecture with residual skip connections to reduce the parameter for the semantic segmentation of exudates in retinal images. The proposed network can robustly segment exudates with high accuracy, making it suitable for diabetic retinopathy screening.
MICROSCOPY RESEARCH AND TECHNIQUE
(2023)
Article
Chemistry, Multidisciplinary
Hadi Hamad, Tahreer Dwickat, Domenico Tegolo, Cesare Valenti
Summary: The study developed an automated method for identifying exudates, allowing for disease warning and patient tracking. By using public domain datasets as benchmarks, the method achieved high levels of sensitivity, specificity, and accuracy through pixel-wise extraction of exudates.
APPLIED SCIENCES-BASEL
(2021)
Article
Medicine, General & Internal
Guanghua Zhang, Bin Sun, Zhixian Chen, Yuxi Gao, Zhaoxia Zhang, Keran Li, Weihua Yang
Summary: This study proposes a deep graph correlation network (DGCN) for automated diabetic retinopathy grading. The DGCN model utilizes a graph convolutional network algorithm to extract inherent correlations from independent retinal image features. Experimental results demonstrate that the DGCN model achieves high accuracy, sensitivity, and specificity on the evaluation datasets.
FRONTIERS IN MEDICINE
(2022)
Article
Multidisciplinary Sciences
Paul Nderitu, Joan M. Nunez do Rio, Rajna Rasheed, Rajiv Raman, Ramachandran Rajalakshmi, Christos Bergeles, Sobha Sivaprasad
Summary: The study found that deep learning-based retinal image gradability predictions can effectively identify patients at risk of sight-threatening diabetic retinopathy, increasing the proportion of gradable images and detection rate of STDR. The performance of capturing retinal images with non-mydriatic handheld cameras outperformed ophthalmologists in terms of gradability.
SCIENTIFIC REPORTS
(2021)
Article
Automation & Control Systems
Muhammad Shujaat, Numan Aslam, Iram Noreen, Muhammad Khurram Ehsan, Muhammad Aasim Qureshi, Aasim Ali, Neelma Naz, Imtisal Qadeer
Summary: The study proposes an intelligent framework to highlight exudate features in fundus images and detect exudates using Alexnet. By developing a new dataset of fundus images from a local hospital, CNN classifier Alexnet achieved high accuracy on both the newly developed local dataset and a benchmark public research dataset.
INTELLIGENT AUTOMATION AND SOFT COMPUTING
(2021)
Article
Engineering, Biomedical
L. Godlin Atlas, K. P. Arjun, K. Sampath Kumar, Rajesh Kumar Dhanaraj, Anand Nayyar
Summary: The range of diseases such as diabetes, hypertension, and vascular occlusions is increasing rapidly in modern society, leading to organ damage. Among them, eye diseases have severe impacts on vision, and early detection and treatment are necessary. Existing strategies have some setbacks, so a deep learning framework has been developed in this study to improve the prediction of retinal hemorrhage.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Computer Science, Information Systems
K. Parthiban, M. Kamarasan
Summary: Diabetic retinopathy is a major cause of preventable blindness for diabetic patients. Regular retinal screening is recommended to detect diabetic retinopathy at an early stage. This study presents an intelligent algorithm based on deep learning for the detection and grading of diabetic retinopathy using retinal fundus images.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Lakshmana Kumar Ramasamy, Shynu Gopalan Padinjappurathu, Seifedine Kadry, Robertas Damasevicius
Summary: A model for diagnosing diabetic retinopathy was developed, extracting and fusing ophthalmoscopic features from retina images and utilizing the SMO classification method, achieving promising diagnostic results.
PEERJ COMPUTER SCIENCE
(2021)
Article
Multidisciplinary Sciences
Niloy Sikder, Mehedi Masud, Anupam Kumar Bairagi, Abu Shamim Mohammad Arif, Abdullah-Al Nahid, Hesham A. Alhumyani
Summary: Diabetic Retinopathy (DR) is a serious global health issue caused by diabetes affecting the retina. This study presents a novel diagnosis method based on decision tree-based ensemble learning technique, achieving 94.20% classification accuracy and 93.51% F-measure on the Asia Pacific Tele-Ophthalmology Society 2019 Blindness Detection dataset.
Article
Multidisciplinary Sciences
Zhihao Che, Fukun Bi, Yu Sun, Weiying Xing, Hui Huang, Xinyue Zhang
Summary: In this study, a dilated residual method based on a feature pyramid network (FPN) is designed to solve the multiscale segmentation problem of mouse retinal images. The results demonstrate that our model achieves the highest precision in both binary segmentation and multiclass semantic segmentation tasks compared to other supervised segmentation methods based on deep learning.
Article
Multidisciplinary Sciences
Ruochen Liu, Song Gao, Hengsheng Zhang, Simin Wang, Lun Zhou, Jiaming Liu
Summary: This paper introduces a deep learning-based algorithm for automatic segmentation of retinal vessels, which achieves better segmentation results with limited dataset capacity. Based on this, a combined diagnosis algorithm for vessel segmentation and diabetic retinopathy classification of retinal images is proposed.
Letter
Ophthalmology
Bhaskar Gupta, James E. Neffendorf, Tom H. Williamson
ACTA OPHTHALMOLOGICA
(2018)
Article
Ophthalmology
James E. Neffendorf, Bhaskar Gupta, Tom H. Williamson
RETINA-THE JOURNAL OF RETINAL AND VITREOUS DISEASES
(2018)
Article
Ophthalmology
Alicja R. Rudnicka, Christopher G. Owen, Roshan A. Welikala, Sarah A. Barman, Peter H. Whincup, David P. Strachan, Michelle P. Y. Chan, Anthony P. Khawaja, David C. Broadway, Robert Luben, Shabina A. Hayat, Kay-Tee Khaw, Paul J. Foster
AMERICAN JOURNAL OF OPHTHALMOLOGY
(2020)
Article
Endocrinology & Metabolism
Robyn J. Tapp, Christopher G. Owen, Sarah A. Barman, Roshan A. Welikala, Paul J. Foster, Peter H. Whincup, David P. Strachan, Alicja R. Rudnicka
Article
Ophthalmology
Mariantonia Ferrara, Alex Mehta, Hamza Qureshi, Peter Avery, David Yorston, D. Alistair Laidlaw, Tomh. Williamson, David H. W. Steel
Summary: The study compared primary rhegmatogenous retinal detachments in phakic and pseudophakic eyes, as well as the differences within phakic eyes with and without cataract. It found significant variations in presenting features between pseudophakic and phakic RD, with some similarities between phakic RD with cataract and pseudophakic RD.
AMERICAN JOURNAL OF OPHTHALMOLOGY
(2021)
Editorial Material
Ophthalmology
Anna Grabowska, James E. Neffendorf, David Yorston, Tom H. Williamson
Article
Ophthalmology
James E. Neffendorf, Neruban Kumaran, Teresa Sandinha, Roger S. Wong, D. Alistair H. Laidlaw, Tom H. Williamson
Summary: In this study of 7532 PPV procedures, intracameral cefuroxime was found to be a safe and effective choice for prophylaxis against endophthalmitis, with a lower incidence compared to subconjunctival administration. There were no cases of cefuroxime toxicity identified, but it was estimated that subconjunctival administration could lead to potentially toxic vitreous drug concentrations in certain cases.
Letter
Ophthalmology
Neruban Kumaran, Giancarlo Dell'Aversana Orabona, Philip J. Banerjee, Tom H. Williamson, David A. H. Laidlaw, Roger Wong
Article
Ophthalmology
Mariantonia Ferrara, Mo Al-Zubaidy, Anna Song, Peter Avery, D. Alistair Laidlaw, Tom H. Williamson, David Yorston, David H. W. Steel
Summary: Age has an influence on the clinical characteristics of primary rhegmatogenous retinal detachments (RRD), with different age groups showing distinct phenotypical differences. This study reveals the existence of various subtypes of RRD.
Article
Endocrinology & Metabolism
Robyn J. Tapp, Christopher G. Owen, Sarah A. Barman, David P. Strachan, Roshan A. Welikala, Paul J. Foster, Peter H. Whincup, Alicja R. Rudnicka
Summary: The study found clear associations between retinal microvascular architecture and cardiometabolic risk factors in patients with diabetes, indicating potential preclinical disease processes and suggesting impaired autoregulation due to hyperglycemia may play a pivotal role in the development of diabetes-related microvascular complications.
Article
Ophthalmology
Mariantonia Ferrara, Anna Song, Mohaimen Al-Zubaidy, Peter Avery, Alistair Laidlaw, Tom H. Williamson, David Yorston, David H. W. Steel
Summary: This study retrospectively analyzed data from two online datasets to assess the effect of sex and laterality on clinical features of primary RRD. The results showed a male predominance and a higher number of right eyes. Males were more commonly pseudophakic and presented with baseline posterior vitreous detachment. Females were associated with myopia, retinal holes, and isolated inferior RD. Right eyes had more foveal involvement and larger retinal tears, while left eyes were more myopic and presented with isolated nasal RD.
Article
Ophthalmology
David Yorston, Paul H. J. Donachie, D. A. Laidlaw, David H. Steel, G. W. Aylward, Tom H. Williamson
Summary: This study aimed to identify factors associated with anatomical outcome after vitrectomy and internal tamponade for rhegmatogenous retinal detachment. The results showed that age, location and extent of retinal breaks, density of silicone oil, and presence of proliferative vitreoretinopathy were associated with increased risk of failure, while C2F6 tamponade, cryotherapy, and 25 G vitrectomy were associated with reduced risk. The risk stratification model indicated that a large portion of patients are at low or moderate risk of failure.
Editorial Material
Ophthalmology
Boon Lin Teh, Steven Toh, Tom H. Williamson, Boguslaw Obara, Jean-Yves Guillemaut, David H. Steel
Article
Ophthalmology
Natalia K. Bober, Neruban Kumaran, Tom H. Williamson
Summary: A retrospective study of 113 patients who underwent pars plana vitrectomy for severe ocular trauma between 1999 and 2018 revealed assault and contusion injuries as the most common mode and type of ocular injury in the cohort. Follow-up showed a varied number of operations required by patients with ocular trauma and a statistically significant improvement in visual acuity.
JOURNAL OF OPHTHALMIC & VISION RESEARCH
(2021)
Article
Computer Science, Information Systems
Roshan Alex Welikala, Paolo Remagnino, Jian Han Lim, Chee Seng Chan, Senthilmani Rajendran, Thomas George Kallarakkal, Rosnah Binti Zain, Ruwan Duminda Jayasinghe, Jyotsna Rimal, Alexander Ross Kerr, Rahmi Amtha, Karthikeya Patil, Wanninayake Mudiyanselage Tilakaratne, John Gibson, Sok Ching Cheong, Sarah Ann Barman
