AIMC Topic: Glaucoma

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An objective structural and functional reference standard in glaucoma.

Scientific reports
The current lack of consensus for diagnosing glaucoma makes it difficult to develop diagnostic tests derived from deep learning (DL) algorithms. In the present study, we propose an objective definition of glaucomatous optic neuropathy (GON) using cle...

A novel retinal ganglion cell quantification tool based on deep learning.

Scientific reports
Glaucoma is a disease associated with the loss of retinal ganglion cells (RGCs), and remains one of the primary causes of blindness worldwide. Major research efforts are presently directed towards the understanding of disease pathogenesis and the dev...

Predicting Glaucoma Development With Longitudinal Deep Learning Predictions From Fundus Photographs.

American journal of ophthalmology
PURPOSE: To assess whether longitudinal changes in a deep learning algorithm's predictions of retinal nerve fiber layer (RNFL) thickness based on fundus photographs can predict future development of glaucomatous visual field defects.

Pathological myopia classification with simultaneous lesion segmentation using deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Pathological myopia (PM) is the seventh leading cause of blindness, with a reported global prevalence up to 3%. Early and automated PM detection from fundus images could aid to prevent blindness in a world population that i...

Assessing Glaucoma Progression Using Machine Learning Trained on Longitudinal Visual Field and Clinical Data.

Ophthalmology
PURPOSE: Rule-based approaches to determining glaucoma progression from visual fields (VFs) alone are discordant and have tradeoffs. To detect better when glaucoma progression is occurring, we used a longitudinal data set of merged VF and clinical da...

Applications of deep learning in detection of glaucoma: A systematic review.

European journal of ophthalmology
Glaucoma is the leading cause of irreversible blindness and disability worldwide. Nevertheless, the majority of patients do not know they have the disease and detection of glaucoma progression using standard technology remains a challenge in clinical...

Automatic Segmentation and Visualization of Choroid in OCT with Knowledge Infused Deep Learning.

IEEE journal of biomedical and health informatics
The choroid provides oxygen and nourishment to the outer retina thus is related to the pathology of various ocular diseases. Optical coherence tomography (OCT) is advantageous in visualizing and quantifying the choroid in vivo. However, its applicati...

Machine Learning Techniques for Ophthalmic Data Processing: A Review.

IEEE journal of biomedical and health informatics
Machine learning and especially deep learning techniques are dominating medical image and data analysis. This article reviews machine learning approaches proposed for diagnosing ophthalmic diseases during the last four years. Three diseases are addre...

Attention-Guided 3D-CNN Framework for Glaucoma Detection and Structural-Functional Association Using Volumetric Images.

IEEE journal of biomedical and health informatics
The direct analysis of 3D Optical Coherence Tomography (OCT) volumes enables deep learning models (DL) to learn spatial structural information and discover new bio-markers that are relevant to glaucoma. Downsampling 3D input volumes is the state-of-a...

Artificial intelligence (AI) impacting diagnosis of glaucoma and understanding the regulatory aspects of AI-based software as medical device.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Glaucoma, the group of eye diseases is characterized by increased intraocular pressure, optic neuropathy and visual field defect patterns. Early and correct diagnosis of glaucoma can prevent irreversible vision loss and glaucomatous structural damage...