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Optic Disk

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CC-TransXNet: a hybrid CNN-transformer network for automatic segmentation of optic cup and optic disk from fundus images.

Medical & biological engineering & computing
Accurate segmentation of the optic disk (OD) and optic cup (OC) regions of the optic nerve head is a critical step in glaucoma diagnosis. Existing architectures based on convolutional neural networks (CNNs) still suffer from insufficient global infor...

MIU-Net: Advanced multi-scale feature extraction and imbalance mitigation for optic disc segmentation.

Neural networks : the official journal of the International Neural Network Society
Pathological myopia is a severe eye condition that can cause serious complications like retinal detachment and macular degeneration, posing a threat to vision. Optic disc segmentation helps measure changes in the optic disc and observe the surroundin...

SLOctolyzer: Fully Automatic Analysis Toolkit for Segmentation and Feature Extracting in Scanning Laser Ophthalmoscopy Images.

Translational vision science & technology
PURPOSE: The purpose of this study was to introduce SLOctolyzer: an open-source analysis toolkit for en face retinal vessels in infrared reflectance scanning laser ophthalmoscopy (SLO) images.

CNN-Based Device-Agnostic Feature Extraction From ONH OCT Scans.

Translational vision science & technology
PURPOSE: Optical coherence tomography (OCT)-derived measurements of the optic nerve head (ONH) from different devices are not interchangeable. This poses challenges to patient follow-up and collaborative studies. Here, we present a device-agnostic me...

Systematic application of saliency maps to explain the decisions of convolutional neural networks for glaucoma diagnosis based on disc and cup geometry.

Biomedical physics & engineering express
This paper systematically evaluates saliency methods as explainability tools for convolutional neural networks trained to diagnose glaucoma using simplified eye fundus images that contain only disc and cup outlines. These simplified images, a methodo...

The Associations Between Myopia and Fundus Tessellation in School Children: A Comparative Analysis of Macular and Peripapillary Regions Using Deep Learning.

Translational vision science & technology
PURPOSE: To evaluate the refractive differences among school-aged children with macular or peripapillary fundus tessellation (FT) distribution patterns, using fundus tessellation density (FTD) quantified by deep learning (DL) technology.

Capsule network-based deep learning for early and accurate diabetic retinopathy detection.

International ophthalmology
Glaucoma, an optic nerve disease resulting in blindness if left untreated, is a difficult condition in healthcare in view of its diagnostic difficulties. Past approaches are based on assessment of the fundus images and the size of the cup and the dis...

Rim learning framework based on TS-GAN: A new paradigm of automated glaucoma screening from fundus images.

Computers in biology and medicine
Glaucoma detection from fundus images often relies on biomarkers such as the Cup-to-Disc Ratio (CDR) and Rim-to-Disc Ratio (RDR). However, precise segmentation of the optic cup and disc is challenging due to low-contrast boundaries and the interferen...

Optimized glaucoma detection using HCCNN with PSO-driven hyperparameter tuning.

Biomedical physics & engineering express
. This study is focused on creating an effective glaucoma detection system employing a Hybrid Centric Convolutional Neural Network (HCCNN) model. By using Particle Swarm Optimization (PSO), classification accuracy is increased and computing complexit...

Robust semi-automatic vessel tracing in the human retinal image by an instance segmentation neural network.

Science advances
Vasculature morphology and hierarchy are essential for blood perfusion. Human retinal circulation is an intricate vascular system emerging and remerging at the optic nerve head (ONH). Tracing retinal vascular branching from ONH can allow detailed mor...