Automated detection and diagnosis of diabetic retinopathy: A comprehensive survey
V Lakshminarayanan, H Kheradfallah, A Sarkar… - Journal of …, 2021 - mdpi.com
Diabetic Retinopathy (DR) is a leading cause of vision loss in the world. In the past few
years, artificial intelligence (AI) based approaches have been used to detect and grade DR …
years, artificial intelligence (AI) based approaches have been used to detect and grade DR …
Artificial intelligence promotes the diagnosis and screening of diabetic retinopathy
X Huang, H Wang, C She, J Feng, X Liu, X Hu… - Frontiers in …, 2022 - frontiersin.org
Deep learning evolves into a new form of machine learning technology that is classified
under artificial intelligence (AI), which has substantial potential for large-scale healthcare …
under artificial intelligence (AI), which has substantial potential for large-scale healthcare …
A foundation model for generalizable disease detection from retinal images
Medical artificial intelligence (AI) offers great potential for recognizing signs of health
conditions in retinal images and expediting the diagnosis of eye diseases and systemic …
conditions in retinal images and expediting the diagnosis of eye diseases and systemic …
Multiresolution knowledge distillation for anomaly detection
Unsupervised representation learning has proved to be a critical component of anomaly
detection/localization in images. The challenges to learn such a representation are two-fold …
detection/localization in images. The challenges to learn such a representation are two-fold …
Code-free deep learning for multi-modality medical image classification
A number of large technology companies have created code-free cloud-based platforms that
allow researchers and clinicians without coding experience to create deep learning …
allow researchers and clinicians without coding experience to create deep learning …
A survey on medical image analysis in diabetic retinopathy
Diabetic Retinopathy (DR) represents a highly-prevalent complication of diabetes in which
individuals suffer from damage to the blood vessels in the retina. The disease manifests …
individuals suffer from damage to the blood vessels in the retina. The disease manifests …
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 …
Deep learning in retinal optical coherence tomography (OCT): A comprehensive survey
Retinal optical coherence tomography (OCT) images provide fundamental information
regarding the health of the posterior eye (eg, the retina and choroid). Thus, the development …
regarding the health of the posterior eye (eg, the retina and choroid). Thus, the development …
Conv-ViT: a convolution and vision transformer-based hybrid feature extraction method for retinal disease detection
The current advancement towards retinal disease detection mainly focused on distinct
feature extraction using either a convolutional neural network (CNN) or a transformer-based …
feature extraction using either a convolutional neural network (CNN) or a transformer-based …
Visual anomaly detection via partition memory bank module and error estimation
P Xing, Z Li - IEEE Transactions on Circuits and Systems for …, 2023 - ieeexplore.ieee.org
Reconstruction method based on the memory module for visual anomaly detection attempts
to narrow the reconstruction error for normal samples while enlarging it for anomalous …
to narrow the reconstruction error for normal samples while enlarging it for anomalous …