PURPOSE: To compare convolutional neural network (CNN) analysis of en face vessel density images to gradient boosting classifier (GBC) analysis of instrument-provided, feature-based optical coherence tomography angiography (OCTA) vessel density measu...
Optical coherence tomography angiography (OCTA) provides a non-invasive method to obtain angiography of the chorioretinal vasculature leading to its recent widespread adoption. With a growing number of studies exploring the use of OCTA, various bioma...
Fundus Image Segmentation (FIS) is an essential procedure for the automated diagnosis of ophthalmic diseases. Recently, deep fully convolutional networks have been widely used for FIS with state-of-the-art performance. The representative deep model i...
Segmentation of retinal vessels is a critical step for the diagnosis of some fundus diseases. To further enhance the performance of vessel segmentation, we propose a method based on a gated skip-connection network with adaptive upsampling (GSAU-Net)...
Experimental biology and medicine (Maywood, N.J.)
Aug 18, 2021
Age-related macular degeneration (AMD) is a leading cause of severe vision loss. With our aging population, it may affect 288 million people globally by the year 2040. AMD progresses from an early and intermediate dry form to an advanced one, which m...
OBJECTIVES: To demonstrate the feasibility of a deep learning-based vascular segmentation tool for UWFA and evaluate its ability to automatically identify quality-optimized phase-specific images.
Computational and mathematical methods in medicine
Aug 9, 2021
METHODS: A new SERR-U-Net framework for retinal vessel segmentation is proposed, which leverages technologies including Squeeze-and-Excitation (SE), residual module, and recurrent block. First, the convolution layers of encoder and decoder are modifi...
Experimental biology and medicine (Maywood, N.J.)
Jul 19, 2021
Optical coherence tomography angiography (OCTA) offers a noninvasive label-free solution for imaging retinal vasculatures at the capillary level resolution. In principle, improved resolution implies a better chance to reveal subtle microvascular dist...
PURPOSE: The segmentation results of retinal blood vessels have a significant impact on the automatic diagnosis of various ophthalmic diseases. In order to further improve the segmentation accuracy of retinal vessels, we propose an improved algorithm...
Accurate segmentation of medical images plays an essential role in their analysis and has a wide range of research and application values in fields of practice such as medical research, disease diagnosis, disease analysis, and auxiliary surgery. In r...