Combining convolutional neural networks and self-attention for fundus diseases identification
K Wang, C Xu, G Li, Y Zhang, Y Zheng, C Sun - Scientific Reports, 2023 - nature.com
… & Fattah, SAAn automatic ocular disease detection scheme from enhanced fundus images
based on ensembling deep cnn networks. In Proceedings of the 2020 11th International …
based on ensembling deep cnn networks. In Proceedings of the 2020 11th International …
Self-speculation of clinical features based on knowledge distillation for accurate ocular disease classification
… A strategy to self-speculate the relevant information from CFPs is necessary for the … KD
inspired activation-based attention transfer between a deeper teacher network and a shallower …
inspired activation-based attention transfer between a deeper teacher network and a shallower …
Automatic diagnosis of macular diseases from OCT volume based on its two-dimensional feature map and convolutional neural network with attention mechanism
Y Sun, H Zhang, X Yao - Journal of Biomedical Optics, 2020 - spiedigitallibrary.org
… to ocular diseases. This greatly increases the analysis burden of the eye specialist, and
this manual interrogation requires expert graders, which is inefficient and prone to yielding …
this manual interrogation requires expert graders, which is inefficient and prone to yielding …
Multi-modal retinal image classification with modality-specific attention network
… , the goal of our ocular disease classification method is to … attention unit, we extend the
self-attention (1) to the region-guided attention module and construct the region-guided attention …
self-attention (1) to the region-guided attention module and construct the region-guided attention …
Discriminative kernel convolution network for multi-label ophthalmic disease detection on imbalanced fundus image dataset
… Deep learning-based ocular image analysis can be used in … -label fundus images whereas
self-supervising learning is … In this manuscript, a novel attention-based model is proposed …
self-supervising learning is … In this manuscript, a novel attention-based model is proposed …
Self-supervised feature learning via exploiting multi-modal data for retinal disease diagnosis
… -supervised feature learning techniques receive a lot of attention, as they do not … diseases
can greatly benefit from another imaging modality, eg, FFA, this paper presents a novel self-…
can greatly benefit from another imaging modality, eg, FFA, this paper presents a novel self-…
CSAUNet: A cascade self-attention u-shaped network for precise fundus vessel segmentation
Z Huang, M Sun, Y Liu, J Wu - Biomedical Signal Processing and Control, 2022 - Elsevier
… Recent studies have verified that the ocular diseases, such as glaucoma, pathologic
myopia and maculopathy, and other related human diseases, such as high blood pressure, …
myopia and maculopathy, and other related human diseases, such as high blood pressure, …
Rotation-oriented collaborative self-supervised learning for retinal disease diagnosis
… Hence, in this paper, our goal is to present a self-supervised method, which learns the …
disease classification tasks. Recently, self-supervised learning has attracted increasing attention …
disease classification tasks. Recently, self-supervised learning has attracted increasing attention …
[HTML][HTML] A Method for Ocular Disease Diagnosis through Visual Prediction Explainability
… interpretation of attention maps, especially if there are multiple levels of attention. Therefore,
… , which combines standard CNNs with a self-attention mechanism. However, when a …
… , which combines standard CNNs with a self-attention mechanism. However, when a …
Optical coherence tomography image based eye disease detection using deep convolutional neural network
Puneet, R Kumar, M Gupta - Health Information Science and Systems, 2022 - Springer
… of AI for the early detection of ocular disorders so that the early detection of disease
diagnosis can be done and the … Output layer passed to fully connected layer for further self-attention. …
diagnosis can be done and the … Output layer passed to fully connected layer for further self-attention. …