Deep learning based joint segmentation and characterization of multi-class retinal fluid lesions on OCT scans for clinical use in anti-VEGF therapy
Background In anti-vascular endothelial growth factor (anti-VEGF) therapy, an accurate
estimation of multi-class retinal fluid (MRF) is required for the activity prescription and …
estimation of multi-class retinal fluid (MRF) is required for the activity prescription and …
Retinal OCT image registration: methods and applications
Retinal image registration is a critical task in the diagnosis and treatment of various eye
diseases. And as a relatively new imaging method, optical coherence tomography (OCT) …
diseases. And as a relatively new imaging method, optical coherence tomography (OCT) …
MsTGANet: Automatic drusen segmentation from retinal OCT images
Drusen is considered as the landmark for diagnosis of AMD and important risk factor for the
development of AMD. Therefore, accurate segmentation of drusen in retinal OCT images is …
development of AMD. Therefore, accurate segmentation of drusen in retinal OCT images is …
Automated computationally intelligent methods for ocular vessel segmentation and disease detection: a review
Ocular diseases are eventually increasing these days that cause partial or complete vision
loss even at an early age, the prominent reason behind this is cardiovascular diseases that …
loss even at an early age, the prominent reason behind this is cardiovascular diseases that …
Semi-supervised capsule cGAN for speckle noise reduction in retinal OCT images
Speckle noise is the main cause of poor optical coherence tomography (OCT) image quality.
Convolutional neural networks (CNNs) have shown remarkable performances for speckle …
Convolutional neural networks (CNNs) have shown remarkable performances for speckle …
Semi-supervised automatic segmentation of layer and fluid region in retinal optical coherence tomography images using adversarial learning
Optical coherence tomography (OCT) is a primary imaging technique for ophthalmic
diagnosis due to its advantages in high resolution and non-invasiveness. Diabetes is a …
diagnosis due to its advantages in high resolution and non-invasiveness. Diabetes is a …
Optical coherence tomography-based deep-learning model for detecting central serous chorioretinopathy
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 …
detachment of the neurosensory retina at the posterior pole. We built a deep learning system …
Boundary aware U-Net for retinal layers segmentation in optical coherence tomography images
Retinal layers segmentation in optical coherence tomography (OCT) images is a critical step
in the diagnosis of numerous ocular diseases. Automatic layers segmentation requires …
in the diagnosis of numerous ocular diseases. Automatic layers segmentation requires …
RAG-FW: A hybrid convolutional framework for the automated extraction of retinal lesions and lesion-influenced grading of human retinal pathology
The identification of retinal lesions plays a vital role in accurately classifying and grading
retinopathy. Many researchers have presented studies on optical coherence tomography …
retinopathy. Many researchers have presented studies on optical coherence tomography …
Automatic segmentation of retinal layer in OCT images with choroidal neovascularization
Age-related macular degeneration is one of the main causes of blindness. However, the
internal structures of retinas are complex and difficult to be recognized due to the occurrence …
internal structures of retinas are complex and difficult to be recognized due to the occurrence …