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Retinal Diseases

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Clinically applicable deep learning for diagnosis and referral in retinal disease.

Nature medicine
The volume and complexity of diagnostic imaging is increasing at a pace faster than the availability of human expertise to interpret it. Artificial intelligence has shown great promise in classifying two-dimensional photographs of some common disease...

Artificial intelligence in retina.

Progress in retinal and eye research
Major advances in diagnostic technologies are offering unprecedented insight into the condition of the retina and beyond ocular disease. Digital images providing millions of morphological datasets can fast and non-invasively be analyzed in a comprehe...

Automated Layer Segmentation of Retinal Optical Coherence Tomography Images Using a Deep Feature Enhanced Structured Random Forests Classifier.

IEEE journal of biomedical and health informatics
Optical coherence tomography (OCT) is a high-resolution and noninvasive imaging modality that has become one of the most prevalent techniques for ophthalmic diagnosis. Retinal layer segmentation is very crucial for doctors to diagnose and study retin...

Structure-Preserving Guided Retinal Image Filtering and Its Application for Optic Disk Analysis.

IEEE transactions on medical imaging
Retinal fundus photographs have been used in the diagnosis of many ocular diseases such as glaucoma, pathological myopia, age-related macular degeneration, and diabetic retinopathy. With the development of computer science, computer aided diagnosis h...

Antiproliferative and anti-apoptotic effect of astaxanthin in an oxygen-induced retinopathy mouse model.

Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
OBJECTIVE: To evaluate the impact of intravitreal (IV) and intraperitoneal (IP) astaxanthin (AST) injections on neovascular development (ND), retinal morphology, and apoptotic activity in a C57BL/6J mouse model with hyperoxia-induced retinopathy (HIR...

Segmentation of Intra-Retinal Cysts From Optical Coherence Tomography Images Using a Fully Convolutional Neural Network Model.

IEEE journal of biomedical and health informatics
Optical coherence tomography (OCT) is an imaging modality that is used extensively for ophthalmic diagnosis, near-histological visualization, and quantification of retinal abnormalities such as cysts, exudates, retinal layer disorganization, etc. Int...

Surrogate-Assisted Retinal OCT Image Classification Based on Convolutional Neural Networks.

IEEE journal of biomedical and health informatics
Optical Coherence Tomography (OCT) is beco-ming one of the most important modalities for the noninvasive assessment of retinal eye diseases. As the number of acquired OCT volumes increases, automating the OCT image analysis is becoming increasingly r...

Feasibility study on robot-assisted retinal vascular bypass surgery in an ex vivo porcine model.

Acta ophthalmologica
PURPOSE: To describe a new robot-assisted surgical system for retinal vascular bypass surgery (RVBS) and to compare the success rate with freehand RVBS.

Multi-level deep supervised networks for retinal vessel segmentation.

International journal of computer assisted radiology and surgery
PURPOSE: Changes in the appearance of retinal blood vessels are an important indicator for various ophthalmologic and cardiovascular diseases, including diabetes, hypertension, arteriosclerosis, and choroidal neovascularization. Vessel segmentation f...

A Discriminatively Trained Fully Connected Conditional Random Field Model for Blood Vessel Segmentation in Fundus Images.

IEEE transactions on bio-medical engineering
GOAL: In this work, we present an extensive description and evaluation of our method for blood vessel segmentation in fundus images based on a discriminatively trained fully connected conditional random field model.