Ophthalmology

Automated detection and classification of early AMD biomarkers using deep learning.

Age-related macular degeneration (AMD) affects millions of people and is a leading cause of blindness throughout the world. Ideally, affected individuals would be identified at an early stage before late sequelae such as outer retinal atrophy or exudative neovascular membranes develop, which could produce irreversible visual loss. Early identification could allow patients to be staged and appropri...

Diabetic retinopathy detection through novel tetragonal local octa patterns and extreme learning machines.

Diabetic retinopathy (DR) is an eye disease that victimize the people suffering from diabetes from many years. The severe form of DR results in form of the blindness that can initially be controlled by the DR-screening oriented treatment. The effective screening programs require the trained human resource that manually grade the fundus images to understand the severity of the disease. But due to t...

Accurate prediction of glaucoma from colour fundus images with a convolutional neural network that relies on active and transfer learning.

PURPOSE: To assess the use of deep learning (DL) for computer-assisted glaucoma identification, and the impact of training using images selected by an...

Development and validation of a deep-learning algorithm for the detection of neovascular age-related macular degeneration from colour fundus photographs.

IMPORTANCE: Detection of early onset neovascular age-related macular degeneration (AMD) is critical to protecting vision.

Development of the Self Optimising Kohonen Index Network (SKiNET) for Raman Spectroscopy Based Detection of Anatomical Eye Tissue.

Raman spectroscopy shows promise as a tool for timely diagnostics via in-vivo spectroscopy of the eye, for a number of ophthalmic diseases. By measuri...

Deep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Grading.

Diabetes is a globally prevalent disease that can cause visible microvascular complications such as diabetic retinopathy and macular edema in the huma...

Implementation of a cloud-based referral platform in ophthalmology: making telemedicine services a reality in eye care.

BACKGROUND: Hospital Eye Services (HES) in the UK face an increasing number of optometric referrals driven by progress in retinal imaging. The Nationa...

Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning.

BACKGROUND: With the advancement of powerful image processing and machine learning techniques, Computer Aided Diagnosis has become ever more prevalent...

Machine Learning-Based Predictive Modeling of Surgical Intervention in Glaucoma Using Systemic Data From Electronic Health Records.

PURPOSE: To predict the need for surgical intervention in patients with primary open-angle glaucoma (POAG) using systemic data in electronic health re...

Deep learning reveals untapped information for local white-matter fiber reconstruction in diffusion-weighted MRI.

PURPOSE: Diffusion-weighted magnetic resonance imaging (DW-MRI) is of critical importance for characterizing in-vivo white matter. Models relating mic...

Exploration of potential key pathways and genes in multiple ocular cancers through bioinformatics analysis.

PURPOSE: Primary cancers of the eye are common in ocular diseases. The objective of this study was to explore the underlying mechanisms and the potent...

Automatic Cataract Classification Using Deep Neural Network With Discrete State Transition.

Cataract is the clouding of lens, which affects vision and it is the leading cause of blindness in the world's population. Accurate and convenient cat...

AI- modelling of molecular identification and feminization of wolbachia infected Aedes aegypti.

BACKGROUND: The genetic control strategies of vector borne diseases includes the replacement of a vector population by "disease-refractory" mosquitoes...

Development of "Predict ME," an online classifier to aid in differentiating diabetic macular edema from pseudophakic macular edema.

PURPOSE: Differentiating the underlying pathology of macular edema in patients with diabetic retinopathy following cataract surgery can be challenging...

Referable diabetic retinopathy identification from eye fundus images with weighted path for convolutional neural network.

Diabetic retinopathy (DR) is the most common cause of blindness in middle-age subjects and low DR screening rates demonstrates the need for an automat...

Future of Radiotherapy in Nasopharyngeal Carcinoma.

Nasopharyngeal carcinoma (NPC) is a malignancy with unique clinical biological profiles such as associated Epstein-Barr virus infection and high radio...

Medical Diagnosis of Cerebral Palsy Rehabilitation Using Eye Images in Machine Learning Techniques.

Cerebral Palsy (CP) is a non progressive neurological disorders commonly associated with a spectrum of developmental disabilities such as strabismus (...

A Large-Scale Database and a CNN Model for Attention-Based Glaucoma Detection.

Glaucoma is one of the leading causes of irreversible vision loss. Many approaches have recently been proposed for automatic glaucoma detection based ...

Deep visual nerve tracking in ultrasound images.

Ultrasound-guided regional anesthesia (UGRA) becomes a standard procedure in surgical operations and pain management, offers the advantages of nerve l...

Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study.

OBJECTIVES: To evaluate the performance of a deep learning based Artificial Intelligence (AI) software for detection of glaucoma from stereoscopic opt...