Framework for dual‐energy‐like chest radiography image synthesis from single‐energy computed tomography based on cycle‐consistent generative adversarial network
Abstract:BackgroundDual‐energy (DE) chest radiography (CXR) enables the selective imaging of two relevant materials, namely, soft tissue and bone structures, to better characterize various chest pathologies (i.e., lung nodule, bony lesions, etc.) and potentially improve CXR‐based diagnosis. Recently, deep‐learning‐based image synthesis techniques have attracted considerable attention as alternatives to existing DE methods (i.e., dual‐exposure‐based and sandwich‐detector‐based methods) because software‐based bone‐only a… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.