Optimization-based algorithms for image reconstruction in multispectral (or photon-counting) computed tomography (MCT) remains a topic of active research. The challenge of optimization-based image reconstruction in MCT stems from the inherently non-linear data model that can lead to a non-convex optimization program for which no mathematically exact solver seems to exist for achieving globally optimal solutions. In this work, based upon a non-linear data model, we design a non-convex optimization program, derive its first-order-optimality conditions, and propose an algorithm to solve the program for image reconstruction in MCT. In addition to consideration of image reconstruction for the standard scan configuration, the emphasis is on investigating the algorithm’s potential for enabling non-standard scan configurations with no or minimum hardware modification to existing CT systems, which has potential practical implications for lowered hardware cost, enhanced scanning flexibili...
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Publication date: Available online 4 January 2018 Source: European Journal of Radiology Author(s): Peiyao Zhang, Jing Wang, Qin Xu, Zhen...
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Dtsch med Wochenschr DOI: 10.1055/s-0043-100054 Hintergrund und Fragestellung Ein etablierter Weg, die optimale Behandlung von Tumorpatien...
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Background Hyperthyroidism is associated with increased thrombotic risk. As contact system activation through formation of neutrophil extrac...
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Editors' Recognition for Reviewing in 2020 No abstract available Establishing Satellite Lung Cancer Screening Sites With Telehealth to A...
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Abstract Silvicultural models are often developed and applied without due consideration of fire modelling. Yet, this information is import...
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Linked Article: Maintz et al. Br J Dermatol 2017; 176:481–487 . from #AlexandrosSfakianakis via Alexandros G.Sfakianakis on Inoreader h...
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