In this study, we propose a method for the automatic diagnosis of five retinal diseases based on an ensemble of two transfer learning models to analyze OCT ...

With the development of convolutional neural network, deep learning has shown its success for retinal disease detection from optical coherence tomography (OCT) ...

Abstract—Optical coherence tomography (OCT) image plays an essential modality role in medical image analysis to diagnose various retinal diseases.

Jan 30, 2023 · This study was designed to apply deep learning models in retinal disease screening and lesion detection based on optical coherence tomography ( ...

Jan 10, 2023 · This study develops an artificially intelligent model. The model is based on a customized 19-layer deep convolutional neural network called VGG-19 architecture.

Nov 11, 2019 · The proposed classification algorithm adopted an ensemble of four classification model instances to identify retinal OCT images, each of which ...

Optical coherence tomography (OCT) is a noninvasive, high-resolution imaging technique widely used in clinical practice to depict the structure of the retina.

The proposed deep-learning algorithm detects three different diseases from features extracted from Optical Coherence Tomography (OCT) images.

In this research, we propose a novel deep learning based model for the accurate prediction of these eye diseases using OCT images. Our methodology involves a ...

We aimed to improve AMD detection using optimized retinal layer segmentation and deep ensemble learning.