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) …

As a non-invasive imaging modality, optical coherence tomography (OCT) can provide
micrometer-resolution 3D images of retinal structures. Therefore it is commonly used in the …

With non-invasive and high-resolution properties, optical coherence tomography (OCT) has
been widely used as a retinal imaging modality for the effective diagnosis of ophthalmic …

Diabetic macular edema (DME) is a highly common cause of vision loss in patients with
diabetes. Optical coherence tomography (OCT) is crucial in classifying DME and tracking the …

Computer-assistant diagnosis of retinal disease relies heavily on the accurate detection of
retinal boundaries and other pathological features such as fluid accumulation. Optical …

AIM To explore a segmentation algorithm based on deep learning to achieve accurate
diagnosis and treatment of patients with retinal fluid. METHODS A two-dimensional (2D) fully …

As a non-invasive imaging modality, optical coherence tomography (OCT) can provide
micrometer-resolution 3D images of retinal structures. These images can help reveal …

Optical coherence tomography (OCT) helps ophthalmologists assess macular edema,
accumulation of fluids, and lesions at microscopic resolution. Quantification of retinal fluids is …

Purpose The purpose of the present study is to develop fast automated quantification of
retinal fluid in optical coherence tomography (OCT) image sets. Methods We developed an …

Evaluation of clinical images is essential for diagnosis in many specialties. Therefore the
development of computer vision algorithms to help analyze biomedical images will be …