An overview of artificial intelligence in diabetic retinopathy and other ocular diseases

B Sheng, X Chen, T Li, T Ma, Y Yang, L Bi… - Frontiers in Public …, 2022 - frontiersin.org
Artificial intelligence (AI), also known as machine intelligence, is a branch of science that
empowers machines using human intelligence. AI refers to the technology of rendering …

Recent developments in detection of central serous retinopathy through imaging and artificial intelligence techniques–a review

SA Hassan, S Akbar, A Rehman, T Saba… - IEEE …, 2021 - ieeexplore.ieee.org
Central Serous Retinopathy (CSR) or Central Serous Chorioretinopathy (CSC) is a
significant disease that causes blindness and vision loss among millions of people …

Optical coherence tomography-based deep-learning model for detecting central serous chorioretinopathy

J Yoon, J Han, JI Park, JS Hwang, JM Han, J Sohn… - Scientific reports, 2020 - nature.com
Central serous chorioretinopathy (CSC) is a common condition characterized by serous
detachment of the neurosensory retina at the posterior pole. We built a deep learning system …

Diabetic retinopathy screening using deep neural network

N Ramachandran, SC Hong, MJ Sime… - Clinical & …, 2018 - Wiley Online Library
Importance There is a burgeoning interest in the use of deep neural network in diabetic
retinal screening. Background To determine whether a deep neural network could …

RAG-FW: A hybrid convolutional framework for the automated extraction of retinal lesions and lesion-influenced grading of human retinal pathology

T Hassan, MU Akram, N Werghi… - IEEE journal of …, 2020 - ieeexplore.ieee.org
The identification of retinal lesions plays a vital role in accurately classifying and grading
retinopathy. Many researchers have presented studies on optical coherence tomography …

Automated diagnoses of age-related macular degeneration and polypoidal choroidal vasculopathy using bi-modal deep convolutional neural networks

Z Xu, W Wang, J Yang, J Zhao, D Ding, F He… - British Journal of …, 2021 - bjo.bmj.com
Aims To investigate the efficacy of a bi-modality deep convolutional neural network (DCNN)
framework to categorise age-related macular degeneration (AMD) and polypoidal choroidal …

Incremental cross-domain adaptation for robust retinopathy screening via Bayesian deep learning

T Hassan, B Hassan, MU Akram… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Retinopathy represents a group of retinal diseases that, if not treated timely, can cause
severe visual impairments or even blindness. Many researchers have developed …

Detection of central serous retinopathy using deep learning through retinal images

SA Hassan, S Akbar, HU Khan - Multimedia Tools and Applications, 2024 - Springer
The human eye is responsible for the visual reorganization of objects in the environment.
The eye is divided into different layers and front/back areas; however, the most important …

A hybrid geometric spatial image representation for scene classification

N Ali, B Zafar, F Riaz, S Hanif Dar, N Iqbal Ratyal… - PloS one, 2018 - journals.plos.org
The recent development in the technology has increased the complexity of image contents
and demand for image classification becomes more imperative. Digital images play a vital …

The European eye epidemiology spectral‐domain optical coherence tomography classification of macular diseases for epidemiological studies

S Gattoussi, GHS Buitendijk, T Peto… - Acta …, 2019 - Wiley Online Library
Purpose The aim of the European Eye Epidemiology (E3) consortium was to develop a
spectral‐domain optical coherence tomography (SD‐OCT)‐based classification for macular …