Fundus image quality assessment: survey, challenges, and future scope
Various ocular diseases, such as cataract, diabetic retinopathy, and glaucoma have affected
a large proportion of the population worldwide. In ophthalmology, fundus photography is …
a large proportion of the population worldwide. In ophthalmology, fundus photography is …
Analysis of diabetic retinopathy (DR) based on the deep learning
If Diabetic Retinopathy (DR) patients do not receive quick diagnosis and treatment, they may
lose vision. DR, an eye disorder caused by high blood glucose, is becoming more prevalent …
lose vision. DR, an eye disorder caused by high blood glucose, is becoming more prevalent …
Data driven approach for eye disease classification with machine learning
Medical health systems have been concentrating on artificial intelligence techniques for
speedy diagnosis. However, the recording of health data in a standard form still requires …
speedy diagnosis. However, the recording of health data in a standard form still requires …
Geometric Correspondence-Based Multimodal Learning for Ophthalmic Image Analysis
Color fundus photography (CFP) and Optical coherence tomography (OCT) images are two
of the most widely used modalities in the clinical diagnosis and management of retinal …
of the most widely used modalities in the clinical diagnosis and management of retinal …
The region of interest localization for glaucoma analysis from retinal fundus image using deep learning
Background and objectives Retinal fundus image analysis without manual intervention has
been rising as an imperative analytical approach for early detection of eye-related diseases …
been rising as an imperative analytical approach for early detection of eye-related diseases …
Retinal image enhancement using cycle-constraint adversarial network
C Wan, X Zhou, Q You, J Sun, J Shen, S Zhu… - Frontiers in …, 2022 - frontiersin.org
Retinal images are the most intuitive medical images for the diagnosis of fundus diseases.
Low-quality retinal images cause difficulties in computer-aided diagnosis systems and the …
Low-quality retinal images cause difficulties in computer-aided diagnosis systems and the …
Multivariate regression-based convolutional neural network model for fundus image quality assessment
Objectively assessing the perceptual quality of an ocular fundus image is essential for the
reliable diagnosis of various ocular diseases. A fair amount of work has been done in this …
reliable diagnosis of various ocular diseases. A fair amount of work has been done in this …
Current state of artificial intelligence applications in ophthalmology and their potential to influence clinical practice
Artificial intelligence (AI) has emerged as a major frontier in healthcare and finds broad
range of applications. It has the potential to revolutionize current procedures of disease …
range of applications. It has the potential to revolutionize current procedures of disease …
Deep learning-based classification of eye diseases using Convolutional Neural Network for OCT images
M Elkholy, MA Marzouk - Frontiers in Computer Science, 2024 - frontiersin.org
Deep learning shows promising results in extracting useful information from medical images.
The proposed work applies a Convolutional Neural Network (CNN) on retinal images to …
The proposed work applies a Convolutional Neural Network (CNN) on retinal images to …
An automatic ROI of the fundus photography
The Region of interest (ROI) of the fundus photography is an important task in medical
image processing. It contains a lot of information related to the diagnosis of the retinal …
image processing. It contains a lot of information related to the diagnosis of the retinal …