Ophthalmology

Automated segmentation of macular edema in OCT using deep neural networks.

Macular edema is an eye disease that can affect visual acuity. Typical disease symptoms include subretinal fluid (SRF) and pigment epithelium detachment (PED). Optical coherence tomography (OCT) has been widely used for diagnosing macular edema because of its non-invasive and high resolution properties. Segmentation for macular edema lesions from OCT images plays an important role in clinical diag...

Detection of smoking status from retinal images; a Convolutional Neural Network study.

Cardiovascular diseases are directly linked to smoking habits, which has both physiological and anatomical effects on the systemic and retinal circulations, and these changes can be detected with fundus photographs. Here, we aimed to 1- design a Convolutional Neural Network (CNN), using retinal photographs, to differentiate between smokers and non-smokers; and 2- use the attention maps to better u...

Counts of mechanical, external configurations compared to computational, internal configurations in natural and artificial systems.

Animal movement encodes information that is meaningfully interpreted by natural counterparts. This is a behavior that roboticists are trying to replic...

A Hybrid Global-Local Representation CNN Model for Automatic Cataract Grading.

Cataract is one of the most serious eye diseases leading to blindness. Early detection and treatment can reduce the rate of blindness in cataract pati...

Defining Image Memorability Using the Visual Memory Schema.

Memorability of an image is a characteristic determined by the human observers' ability to remember images they have seen. Yet recent work on image me...

BoSR: A CNN-based aurora image retrieval method.

The deep learning models especially the CNN have achieved amazing performance on natural image retrieval. However, remote sensing images captured with...

Artificial intelligence using deep learning to screen for referable and vision-threatening diabetic retinopathy in Africa: a clinical validation study.

BACKGROUND: Radical measures are required to identify and reduce blindness due to diabetes to achieve the Sustainable Development Goals by 2030. There...

Localizing epileptogenic regions using high-frequency oscillations and machine learning.

Pathological high frequency oscillations (HFOs) are putative neurophysiological biomarkers of epileptogenic brain tissue. Utilizing HFOs for epilepsy ...

Deep learning in ophthalmology: The technical and clinical considerations.

The advent of computer graphic processing units, improvement in mathematical models and availability of big data has allowed artificial intelligence (...

JointRCNN: A Region-Based Convolutional Neural Network for Optic Disc and Cup Segmentation.

OBJECTIVE: The purpose of this paper is to propose a novel algorithm for joint optic disc and cup segmentation, which aids the glaucoma detection.

Machine learning accurately classifies age of toddlers based on eye tracking.

How people extract visual information from complex scenes provides important information about cognitive processes. Eye tracking studies that have use...

Artificial Intelligence and Optical Coherence Tomography Imaging.

This review article aimed to highlight the application and use of artificial intelligence (AI) in optical coherence tomography (OCT) imaging in ophtha...

[Can Big Data change our practices?].

The European Medicines Agency has defined Big Data by the "3 V's": Volume, Velocity and Variety. These large databases allow access to real life data ...

Robust optic disc and cup segmentation with deep learning for glaucoma detection.

Glaucoma is rated as the leading cause of irreversible vision loss worldwide. Early detection of glaucoma is important for providing timely treatment ...

Weakly supervised lesion localization for age-related macular degeneration detection using optical coherence tomography images.

Age-related macular degeneration (AMD) is the main cause of irreversible blindness among the elderly and require early diagnosis to prevent vision los...

BTS-DSN: Deeply supervised neural network with short connections for retinal vessel segmentation.

BACKGROUND AND OBJECTIVE: The condition of vessel of the human eye is an important factor for the diagnosis of ophthalmological diseases. Vessel segme...

Vision-Based Robot Navigation through Combining Unsupervised Learning and Hierarchical Reinforcement Learning.

Extensive studies have shown that many animals' capability of forming spatial representations for self-localization, path planning, and navigation rel...

Validation of a Deep Learning Model to Screen for Glaucoma Using Images from Different Fundus Cameras and Data Augmentation.

PURPOSE: To validate a deep residual learning algorithm to diagnose glaucoma from fundus photography using different fundus cameras at different insti...

Patient-attentive sequential strategy for perimetry-based visual field acquisition.

Perimetry is a non-invasive clinical psychometric examination used for diagnosing ophthalmic and neurological conditions. At its core, perimetry relie...

Classifying major depression patients and healthy controls using EEG, eye tracking and galvanic skin response data.

OBJECTIVE: Major depression disorder (MDD) is one of the most prevalent mental disorders worldwide. Diagnosing depression in the early stage is crucia...