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Diagnostic and Interventional Radiology

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Future scenarios and opportunities for interventional radiology in the post COVID-19 era

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A review on the use of artificial intelligence for medical imaging of the lungs of patients with coronavirus disease 2019‎

Ito, Rintaro; Iwano, Shingo; Naganawa, Shinji

Technical background of a novel detector-based approach energy computed tomography‎

Hokamp, Nils Grosse; Maintz, David; Shapira, Nadav; et al.

Radiomics-based nomogram using CT imaging for noninvasive preoperative prediction of early recurrence in patients with hepatocellular carcinoma‎

Zhu, Hong-Bo; Zheng, Ze-Yu; Zhao, Heng; et al.

Comparison of semi-automatic and deep learning-based automatic methods for liver segmentation in living liver transplant donors‎

Kavur, A. Emre; Gezer, Naciye Sinem; Baris, Mustafa; et al.

Ethical considerations for artificial intelligence: an overview of the current radiology landscape

Tugba Akinci D'Antonoli

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Radiological approach to COVID-19 pneumonia with an emphasis on chest CT

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A review on the use of artificial intelligence for medical imaging of the lungs of patients with coronavirus disease 2019

By: Ito, R; Iwano, S and Naganawa, S

COVID-19 S: A new proposal for diagnosis and structured reporting of COVID-19 on computed tomography imaging

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CT findings of COVID-19 in follow-up: comparison between progression and recovery

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Rare CT feature in a COVID-19 patient: cavitation

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Differentiation of adrenal adenomas from adrenal metastases in single-phased staging dual-energy CT and radiomics

Moritz T. Winkelmann, Sebastian Gassenmaier, Sven S. Walter, Christoph Artzner, Felix Lades, Sebastian Faby, Konstantin Nikolaou, Malte N. Bongers

(Diagn Interv Radiol 2022; 28: 208-216) DOI: 10.5152/dir.2022.21691

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