IEEE journal of biomedical and health informatics
Dec 1, 2020
Deep learning has achieved remarkable success in the optical coherence tomography (OCT) image classification task with substantial labelled B-scan images available. However, obtaining such fine-grained expert annotations is usually quite difficult an...
Disease classification and lesion segmentation of retinal optical coherence tomography images play important roles in ophthalmic computer-aided diagnosis. However, existing methods achieve the two tasks separately, which is insufficient for clinical ...
Journal of the Chinese Medical Association : JCMA
Nov 1, 2020
BACKGROUND: Optical coherence tomography (OCT) is considered as a sensitive and noninvasive tool to evaluate the macular lesions. In patients with diabetes mellitus (DM), the existence of diabetic macular edema (DME) can cause significant vision impa...
PURPOSE: Differentiating the underlying pathology of macular edema in patients with diabetic retinopathy following cataract surgery can be challenging. In 2015, Munk and colleagues trained and tested a machine learning classifier which uses optical c...
Translational vision science & technology
Oct 1, 2020
PURPOSE: We proposed a deep convolutional neural network (CNN), named Retinal Fluid Segmentation Network (ReF-Net), to segment retinal fluid in diabetic macular edema (DME) in optical coherence tomography (OCT) volumes.
Vision loss caused by diabetic macular edema (DME) can be prevented by early detection and laser photocoagulation. As there is no comprehensive detection technique to recognize NPA, we proposed an automatic detection method of NPA on fundus fluoresce...
IMPORTANCE: Large amounts of optical coherence tomographic (OCT) data of diabetic macular edema (DME) are acquired, but many morphologic features have yet to be identified and quantified.
OBJECTIVE: Automatic diabetic retinopathy screening system based on neural networks has been used to detect diabetic retinopathy (DR). However, there is no quantitative synthesis of performance of these methods. We aimed to estimate the sensitivity a...
Translational vision science & technology
May 1, 2020
PURPOSE: To assess whether a generative adversarial network (GAN) could synthesize realistic optical coherence tomography (OCT) images that satisfactorily serve as the educational images for retinal specialists, and the training datasets for the clas...