AIMC Topic: Fundus Oculi

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Quality and content analysis of fundus images using deep learning.

Computers in biology and medicine
Automatic retinal image analysis has remained an important topic of research in the last ten years. Various algorithms and methods have been developed for analysing retinal images. The majority of these methods use public retinal image databases for ...

A Novel Weakly Supervised Multitask Architecture for Retinal Lesions Segmentation on Fundus Images.

IEEE transactions on medical imaging
Obtaining the complete segmentation map of retinal lesions is the first step toward an automated diagnosis tool for retinopathy that is interpretable in its decision-making. However, the limited availability of ground truth lesion detection maps at a...

CNNs for automatic glaucoma assessment using fundus images: an extensive validation.

Biomedical engineering online
BACKGROUND: Most current algorithms for automatic glaucoma assessment using fundus images rely on handcrafted features based on segmentation, which are affected by the performance of the chosen segmentation method and the extracted features. Among ot...

Patch-Based Output Space Adversarial Learning for Joint Optic Disc and Cup Segmentation.

IEEE transactions on medical imaging
Glaucoma is a leading cause of irreversible blindness. Accurate segmentation of the optic disc (OD) and optic cup (OC) from fundus images is beneficial to glaucoma screening and diagnosis. Recently, convolutional neural networks demonstrate promising...

Glaucoma Diagnosis with Machine Learning Based on Optical Coherence Tomography and Color Fundus Images.

Journal of healthcare engineering
This study aimed to develop a machine learning-based algorithm for glaucoma diagnosis in patients with open-angle glaucoma, based on three-dimensional optical coherence tomography (OCT) data and color fundus images. In this study, 208 glaucomatous an...

Application of a deep convolutional neural network in the diagnosis of neonatal ocular fundus hemorrhage.

Bioscience reports
There is a disparity between the increasing application of digital retinal imaging to neonatal ocular screening and slowly growing number of pediatric ophthalmologists. Assistant tools that can automatically detect ocular disorders may be needed. In ...

Weakly Supervised Lesion Detection From Fundus Images.

IEEE transactions on medical imaging
Early diagnosis and continuous monitoring of patients suffering from eye diseases have been major concerns in the computer-aided detection techniques. Detecting one or several specific types of retinal lesions has made a significant breakthrough in c...

Automated glaucoma diagnosis using bit-plane slicing and local binary pattern techniques.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: Glaucoma is a ocular disorder which causes irreversible damage to the retinal nerve fibers. The diagnosis of glaucoma is important as it may help to slow down the progression. The available clinical methods and imaging techn...

Deep Learning for Image Quality Assessment of Fundus Images in Retinopathy of Prematurity.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Accurate image-based medical diagnosis relies upon adequate image quality and clarity. This has important implications for clinical diagnosis, and for emerging methods such as telemedicine and computer-based image analysis. In this study, we trained ...