AIMC Topic: Optic Disk
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Joint optic disk and cup segmentation for glaucoma screening using a region-based deep learning network.
Eye (London, England)
Apr 18, 2022
OBJECTIVES: To develop and validate an end-to-end region-based deep convolutional neural network (R-DCNN) to jointly segment the optic disc (OD) and optic cup (OC) in retinal fundus images for precise cup-to-disc ratio (CDR) measurement and glaucoma ...
A deep learning approach for detection of shallow anterior chamber depth based on the hidden features of fundus photographs.
Computer methods and programs in biomedicine
Mar 6, 2022
BACKGROUND AND OBJECTIVES: Patients with angle-closure glaucoma (ACG) are asymptomatic until they experience a painful attack. Shallow anterior chamber depth (ACD) is considered a significant risk factor for ACG. We propose a deep learning approach t...
Graph-Based Region and Boundary Aggregation for Biomedical Image Segmentation.
IEEE transactions on medical imaging
Mar 2, 2022
Segmentation is a fundamental task in biomedical image analysis. Unlike the existing region-based dense pixel classification methods or boundary-based polygon regression methods, we build a novel graph neural network (GNN) based deep learning framewo...
Policy-Driven, Multimodal Deep Learning for Predicting Visual Fields from the Optic Disc and OCT Imaging.
Ophthalmology
Feb 21, 2022
PURPOSE: To develop and validate a deep learning (DL) system for predicting each point on visual fields (VFs) from disc and OCT imaging and derive a structure-function mapping.
Segmentation and Classification of Glaucoma Using U-Net with Deep Learning Model.
Journal of healthcare engineering
Feb 16, 2022
Glaucoma is the second most common cause for blindness around the world and the third most common in Europe and the USA. Around 78 million people are presently living with glaucoma (2020). It is expected that 111.8 million people will have glaucoma b...
Evaluations of Deep Learning Approaches for Glaucoma Screening Using Retinal Images from Mobile Device.
Sensors (Basel, Switzerland)
Feb 14, 2022
Glaucoma is a silent disease that leads to vision loss or irreversible blindness. Current deep learning methods can help glaucoma screening by extending it to larger populations using retinal images. Low-cost lenses attached to mobile devices can inc...
Multiple instance learning detects peripheral arterial disease from high-resolution color fundus photography.
Scientific reports
Jan 26, 2022
Peripheral arterial disease (PAD) is caused by atherosclerosis and is a common disease of the elderly leading to excess morbidity and mortality. Early PAD diagnosis is important, as the only available causal therapy is addressing risk factors like sm...
An Efficient Deep Learning Approach to Automatic Glaucoma Detection Using Optic Disc and Optic Cup Localization.
Sensors (Basel, Switzerland)
Jan 7, 2022
Glaucoma is an eye disease initiated due to excessive intraocular pressure inside it and caused complete sightlessness at its progressed stage. Whereas timely glaucoma screening-based treatment can save the patient from complete vision loss. Accurate...
Weakly Supervised Sensitive Heatmap framework to classify and localize diabetic retinopathy lesions.
Scientific reports
Dec 8, 2021
Vision loss happens due to diabetic retinopathy (DR) in severe stages. Thus, an automatic detection method applied to diagnose DR in an earlier phase may help medical doctors to make better decisions. DR is considered one of the main risks, leading t...
A Novel Context Aware Joint Segmentation and Classification Framework for Glaucoma Detection.
Computational and mathematical methods in medicine
Nov 5, 2021
Glaucoma is a chronic ocular disease characterized by damage to the optic nerve resulting in progressive and irreversible visual loss. Early detection and timely clinical interventions are critical in improving glaucoma-related outcomes. As a typical...
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