Holographic displays promise unprecedented capabilities for direct-view displays as well as virtual and augmented reality applications. However, one of the biggest challenges for computer-generated holography (CGH) is the fundamental tradeoff between algorithm runtime and achieved image quality, which has prevented high-quality holographic image synthesis at fast speeds. Moreover, the image quality achieved by most holographic displays is low, due to the mismatch between the optical wave propagation of the display and its simulated model. Here, we develop an algorithmic CGH framework that achieves unprecedented image fidelity and real-time framerates. Our framework comprises several parts, including a novel camera-in-the-loop optimization strategy that allows us to either optimize a hologram directly or train an interpretable model of the optical wave propagation and a neural network architecture that represents the first CGH algorithm capable of generating full-color high-quality holographic images at 1080p resolution in real time.
Individuals with ultrasonographically detected NAFLD have an elevated 10-year risk of developing CHD as estimated using FRS. Furthermore, NAFLD was found to be independently related to the risk of developing CHD, regardless of classical risk factors and other components of MS.
Aim:The cardio-ankle vascular index (CAVI) reflects overall arterial stiffness from the aorta to the ankle, independent of blood pressure. We aimed to investigate the association of fat burden assessed by visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT) and epicardial adipose tissue (EAT) with CAVI in an asymptomatic population.
Patients with NAFLD are at a high risk of carotid atherosclerosis regardless of metabolic syndrome and classical cardiovascular risk factors. Therefore, the detection of NAFLD should alert to the existence of an increased cardiovascular risk. Moreover, NAFLD might be an independent risk factor for cardiovascular disease.
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