Artificial intelligence and deep learning in ophthalmology-present and future

AD Moraru, D Costin, RL Moraru… - Experimental and …, 2020 - spandidos-publications.com
Since its introduction in 1959, artificial intelligence technology has evolved rapidly and
helped benefit research, industries and medicine. Deep learning, as a process of artificial …

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 …

Robust total retina thickness segmentation in optical coherence tomography images using convolutional neural networks

FG Venhuizen, B van Ginneken, B Liefers… - Biomedical optics …, 2017 - opg.optica.org
We developed a fully automated system using a convolutional neural network (CNN) for total
retina segmentation in optical coherence tomography (OCT) that is robust to the presence of …

Joint segmentation and quantification of chorioretinal biomarkers in optical coherence tomography scans: A deep learning approach

B Hassan, S Qin, T Hassan, R Ahmed… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In ophthalmology, chorioretinal biomarkers (CRBMs) play a significant role in detecting,
quantifying, and ameliorating the treatment of chronic eye conditions. Optical coherence …

Classification of diabetes-related retinal diseases using a deep learning approach in optical coherence tomography

O Perdomo, H Rios, FJ Rodríguez, S Otálora… - Computer methods and …, 2019 - Elsevier
Abstract Background and objectives: Spectral Domain Optical Coherence Tomography (SD-
OCT) is a volumetric imaging technique that allows measuring patterns between layers such …

Automated diagnosis of diabetic retinopathy using clinical biomarkers, optical coherence tomography, and optical coherence tomography angiography

HS Sandhu, M Elmogy, AT Sharafeldeen… - American journal of …, 2020 - Elsevier
Purpose To determine if combining clinical, demographic, and imaging data improves
automated diagnosis of nonproliferative diabetic retinopathy (NPDR). Design Cross …

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 …

Computer aided diagnosis of diabetic macular edema in retinal fundus and OCT images: A review

KC Pavithra, P Kumar, M Geetha… - Biocybernetics and …, 2023 - Elsevier
Abstract Diabetic Macular Edema (DME) is a potentially blinding consequence of Diabetic
Retinopathy (DR) as well as the leading cause of vision loss in diabetics. DME is …

Deep learning-based automatic detection of central serous retinopathy using optical coherence tomographic images

SAE Hassan, S Akbar, S Gull… - 2021 1st International …, 2021 - ieeexplore.ieee.org
Central Serous Retinopathy (CSR), also known as Central Serous Chorioretinopathy (CSC),
occurs due to the clotting of fluids behind the retinal surface. The retina is composed of thin …

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 …