Vision language models in ophthalmology
Summary Vision Language Models offer the potential to assist and streamline the existing
clinical workflow in ophthalmology, whether previsit, during, or post-visit. There are …
clinical workflow in ophthalmology, whether previsit, during, or post-visit. There are …
Oct-based deep-learning models for the identification of retinal key signs
I Leandro, B Lorenzo, M Aleksandar, M Dario… - Scientific Reports, 2023 - nature.com
A new system based on binary Deep Learning (DL) convolutional neural networks has been
developed to recognize specific retinal abnormality signs on Optical Coherence …
developed to recognize specific retinal abnormality signs on Optical Coherence …
Development of a generative deep learning model to improve epiretinal membrane detection in fundus photography
Background The epiretinal membrane (ERM) is a common retinal disorder characterized by
abnormal fibrocellular tissue at the vitreomacular interface. Most patients with ERM are …
abnormal fibrocellular tissue at the vitreomacular interface. Most patients with ERM are …
Developing a transparent diagnosis model for diabetic retinopathy using explainable AI
Diabetic retinopathy is a leading cause of vision complications and partially sighted which
pose considerable diagnostic difficulties because of its diverse and varying symptoms …
pose considerable diagnostic difficulties because of its diverse and varying symptoms …
Validation of neuron activation patterns for artificial intelligence models in oculomics
S An, D Squirrell - Scientific Reports, 2024 - nature.com
Recent advancements in artificial intelligence (AI) have prompted researchers to expand
into the field of oculomics; the association between the retina and systemic health. Unlike …
into the field of oculomics; the association between the retina and systemic health. Unlike …
Computer-aided multi-label retinopathy diagnosis via inter-disease graph regularization
TS Elsayed, MA Rushdi - Biomedical Signal Processing and Control, 2024 - Elsevier
Computer-aided diagnosis (CAD) of retinal fundus diseases is crucial for effective treatment
planning and avoidance of vision deterioration and loss. Most existing CAD systems are …
planning and avoidance of vision deterioration and loss. Most existing CAD systems are …
Ocular Disease Recognition via Differential Privacy and Unsupervised Domain Regularizer
Z Tang, HS Wong, Z Yu - IEEE Signal Processing Letters, 2023 - ieeexplore.ieee.org
Adopting deep learning in early fundus screening images benefits ocular disease
recognition and helps patients avoid blindness in recent years. The robust data …
recognition and helps patients avoid blindness in recent years. The robust data …
OCT-based deep-learning models for the identification of retinal key signs
L Inferrera, L Borsatti, A Miladinović, D Marangoni… - Scientific Reports, 2023 - arts.units.it
A new system based on binary Deep Learning (DL) convolutional neural networks has been
developed to recognize specific retinal abnormality signs on Optical Coherence …
developed to recognize specific retinal abnormality signs on Optical Coherence …
[PDF][PDF] Improving Out-of-Distribution Detection Performance using Synthetic Outlier Exposure Generated by Visual Foundation Models.
Real-world deep learning applications often encounter out-of-distribution (OOD) samples
that do not belong to the label spaces of the training dataset. Therefore, neural networks …
that do not belong to the label spaces of the training dataset. Therefore, neural networks …
A Comprehensive Approach for Predicting Different Types of Retinal Detachment with ML Algorithms
The usage of neural networks to image processing has grown in popularity as computer
technology and hardware have advanced over time. Soon, DL attracted the attention of …
technology and hardware have advanced over time. Soon, DL attracted the attention of …