Arama

EISSN 1305-3612

IMPACT FACTOR: 2.63 5 YEAR IF: 2.59 SCOPUS CITESCORE: 3.9

Diagnostic and Interventional Radiology

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HIGHLY CITED ARTICLES

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

By: Guneyli, S; Atceken, Z; Dogan, H; et al.

Interventional radiology and COVID-19: evidence-based measures to limit transmission

By: Chandy, PE; Nasir, MU; Srinivasan, S; et al.

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

By: Hokamp, NG; Maintz, D; Shapira, N; et al.

How imaging should properly be used in COVID-19 outbreak: an Italian experience

By: Sverzellati, N; Milone, F and Balbi, M

Management strategy of novel coronavirus (COVID-19) pneumonia in the radiology department: a Chinese experience

By: An, P; Ye, YJ; Chen, YT; et al.

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

By: Kavur, AE; Gezer, NS; Baris, M; et al.

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

By: Gezer, NS; Ergan, B; Baris, MM; et al.

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

By: Guan, CS; Wei, LG; Xie, RM; et al.

Rare CT feature in a COVID-19 patient: cavitation

By: Xu, ZF; Pan, AZ and Zhou, HL

EDITOR'S PICK

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

Maria Abadal, Jose; Gonzalez-Nieto, Jimena; Lopez-Zarraga, Fernando; et al.

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

COVID-19 ARTICLES

COVID-19 radiology CT personnel management

By: Özdemir et al.

Future of IR in the post COVID-19 era

By: Abadal et al.

CT findings to predict hospitalization and intensive care need for COVID-19

By: Tekcan Sanli et al.

Application of percutaneous transluminal sharp recanalization in TIPS

By: Li et al.

Comparison of laboratory-confirmed and clinically diagnosed COVID-19 patients

By: Kuzan et al.

Low-dose chest CT to diagnose COVID-19

By: Aslan et al.

Quantitative chest CT in COVID-19

By: Ufuk et al.

Vascular changes in COVID-19 pneumonia

By: Tekcan Şanlı and Yıldırım.

Use of deep learning in chest X-ray images of COVID-19 patients

By: Blain et al.

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Effect of acquisition techniques, latest kernels, and advanced monoenergetic postprocessing on stent visualization with 3rd generation dual source CT

Christoph Artzner, Gerd Grözinger, Manuel Kolb, Sven S. Walter, Sergios Gatidis, Malte N. Bongers

(Diagn Interv Radiol 2020; 1: -) DOI: 10.5152/dir.2022.21107

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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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