AIMC Topic: Fundus Oculi

Clear Filters Showing 381 to 390 of 512 articles

An ensemble deep learning based approach for red lesion detection in fundus images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Diabetic retinopathy (DR) is one of the leading causes of preventable blindness in the world. Its earliest sign are red lesions, a general term that groups both microaneurysms (MAs) and hemorrhages (HEs). In daily clinical ...

Accuracy of deep learning, a machine-learning technology, using ultra-wide-field fundus ophthalmoscopy for detecting rhegmatogenous retinal detachment.

Scientific reports
Rhegmatogenous retinal detachment (RRD) is a serious condition that can lead to blindness; however, it is highly treatable with timely and appropriate treatment. Thus, early diagnosis and treatment of RRD is crucial. In this study, we applied deep le...

Decision Support System for Detection of Papilledema through Fundus Retinal Images.

Journal of medical systems
A condition in which the optic nerve inside the eye is swelled due to increased intracranial pressure is known as papilledema. The abnormalities due to papilledema such as opacification of Retinal Nerve Fiber Layer (RNFL), dilated optic disc capillar...

Detection of exudates in fundus photographs using deep neural networks and anatomical landmark detection fusion.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Diabetic retinopathy is one of the leading disabling chronic diseases and one of the leading causes of preventable blindness in developed world. Early diagnosis of diabetic retinopathy enables timely treatment and in order t...

Retinal vessel segmentation in colour fundus images using Extreme Learning Machine.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Attributes of the retinal vessel play important role in systemic conditions and ophthalmic diagnosis. In this paper, a supervised method based on Extreme Learning Machine (ELM) is proposed to segment retinal vessel. Firstly, a set of 39-D discriminat...

Fast Convolutional Neural Network Training Using Selective Data Sampling: Application to Hemorrhage Detection in Color Fundus Images.

IEEE transactions on medical imaging
Convolutional neural networks (CNNs) are deep learning network architectures that have pushed forward the state-of-the-art in a range of computer vision applications and are increasingly popular in medical image analysis. However, training of CNNs is...

A Hybrid Swarm Algorithm for optimizing glaucoma diagnosis.

Computers in biology and medicine
Glaucoma is among the most common causes of permanent blindness in human. Because the initial symptoms are not evident, mass screening would assist early diagnosis in the vast population. Such mass screening requires an automated diagnosis technique....

[Focusing on the challenges and opportunities of optical coherence tomography in the diagnosis and treatment of fundus diseases].

[Zhonghua yan ke za zhi] Chinese journal of ophthalmology
Optical coherence tomography (OCT), with its advantages of non-invasiveness, non-contact, rapid imaging, and high resolution, has become an indispensable core imaging tool in the diagnosis and treatment of fundus diseases. It provides clinicians with...