optical coherence tomography angiography

We designed an end-to-end deep neural network (DNN) framework with a two-staged adversarial training scheme to reconstruct fully-sampled, high-quality (8 repeated B-scans) angiograms from their corresponding undersampled, low-quality (2 repeated B-scans) counterparts by successively enhancing the pixel resolution and the image quality. Herein, we propose an integrated DL method to simultaneously tackle both factors and further enhance the reconstruction performance in speed and quality. While these approaches have shown promising results, they provide limited solutions that only partially account for the OCTA scanning mechanism. They achieve faster acquisition using two independent reconstructing approaches: high-quality angiograms from a few repeated B-scans and high-resolution angiograms from undersampled data. Recently, deep learning (DL)-based methods have gained attention in accelerating the OCTA acquisition process. The current protocols require high sampling density and multiple acquisitions of cross-sectional B-scans to form one image frame, resulting in low acquisition speed. One primary technical drawback for OCTA, however, is its imaging speed. fluorescein angiography) and review clinical studies demonstrating the utility of OCTA for research and clinical practice.Label-free optical coherence tomography angiography (OCTA) has become a premium imaging tool in clinics to obtain structural and functional information of microvasculatures. In this review, we will discuss the methods used to create OCTA images, the practical applications of OCTA in light of invasive dye-imaging studies (e.g. Correspondingly, OCTA has been used to evaluate a spectrum of retinal vascular diseases including diabetic retinopathy (DR), retinal venous occlusion (RVO), uveitis, retinal arterial occlusion, and age-related macular degeneration among others. More importantly, OCTA provides depth-resolved information that has never before been available. OCTA demonstrates many important clinical findings including areas of macular telangiectasia, impaired perfusion, microaneurysms, capillary remodeling, some types of intraretinal fluid, and neovascularization among many others. This unprecedented resolution coupled with the simple, fast and non-invasive imaging platform have allowed a host of basic and clinical research applications. In many cases, these images are approaching histology level resolution. This motion-contrast imaging provides reliable, high resolution, and non-invasive images of the retinal vasculature in an efficient manner. red blood cells are moving, but neurosensory tissue is static), OCTA images are essentially motion-contrast images. Since the intensity and phase of backscattered light from retinal tissue varies based on the intrinsic movement of the tissue (e.g. OCTA images are based on the variable backscattering of light from the vascular and neurosensory tissue in the retina. OCT-Angiography (OCTA) is one such method that has rapidly gained clinical acceptance since it was approved by the FDA in late 2016. Advances in OCT technology have allowed for the creation of novel OCT-based methods. OCT has revolutionized the practice of ophthalmology over the past 10–20 years.

Optical coherence tomography angiography