PURPOSE: To assess the use of deep learning (DL) for computer-assisted glaucoma identification, and the impact of training using images selected by an active learning strategy, which minimizes labelling cost. Additionally, this study focuses on the e...
BACKGROUND: Hospital Eye Services (HES) in the UK face an increasing number of optometric referrals driven by progress in retinal imaging. The National Health Service (NHS) published a 10-year strategy (NHS Long-Term Plan) to transform services to me...
BMC medical informatics and decision making
Jul 17, 2019
BACKGROUND: With the advancement of powerful image processing and machine learning techniques, Computer Aided Diagnosis has become ever more prevalent in all fields of medicine including ophthalmology. These methods continue to provide reliable and s...
Glaucoma is one of the leading causes of irreversible vision loss. Many approaches have recently been proposed for automatic glaucoma detection based on fundus images. However, none of the existing approaches can efficiently remove high redundancy in...
Optical coherence tomography (OCT) based measurements of retinal layer thickness, such as the retinal nerve fibre layer (RNFL) and the ganglion cell with inner plexiform layer (GCIPL) are commonly employed for the diagnosis and monitoring of glaucoma...
Glaucoma is the leading cause of irreversible blindness worldwide. Early detection is of utmost importance as there is abundant evidence that early treatment prevents disease progression, preserves vision, and improves patients' long-term quality of ...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Apr 5, 2019
Glaucoma is rated as the leading cause of irreversible vision loss worldwide. Early detection of glaucoma is important for providing timely treatment and minimizing the vision loss. In this paper, we developed a robust segmentation method for optic d...
PURPOSE: To validate a deep residual learning algorithm to diagnose glaucoma from fundus photography using different fundus cameras at different institutes.