DOSEGAN: A GENERATIVE ADVERSARIAL NETWORK FOR SYNTHETIC DOSE PREDICTION USING ATTENTION-GATED DISCRIMINATION AND GENERATION

DoseGAN: a generative adversarial network for synthetic dose prediction using attention-gated discrimination and generation

Abstract Deep learning algorithms have recently been developed that utilize patient Airliner Model Kits anatomy and raw imaging information to predict radiation dose, as a means to increase treatment planning efficiency and improve radiotherapy plan quality.Current state-of-the-art techniques rely on convolutional neural networks (CNNs) that use pi

read more


DOES IT MATTER WHERE I LIVE? COMPARING THE IMPACT OF HOUSING QUALITY ON CHILD DEVELOPMENT IN SLUM AND NON-SLUM AREAS IN GHANA

Deteriorating physical characteristics and limited access to social services are said to typify a substantial number of the housing types in Ghana.The impact of these on vulnerable groups such as children remains largely unresearched.This paper comparesthe quality of houses in a slum (Old Fadama) and IMMUNOL a non-slum (Asylum Down) community and i

read more

Silica Nanoparticle-Infused Omniphobic Polyurethane Foam with Bacterial Anti-Adhesion and Antifouling Properties for Hygiene Purposes

In this study, a method for preventing cross-infection through the surface coating treatment of polyurethane (PU) foam using functionalized silica nanoparticles was developed.Experimental Cacao results confirmed that the fabricated PU foam exhibited omniphobic characteristics, demonstrating strong resistance to both polar and nonpolar contaminants.

read more