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EISSN 1305-3612

5-YEAR IMPACT FACTOR: 2:093 IMPACT FACTOR: 1.871

Diagnostic and Interventional Radiology

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HIGHLY CITED ARTICLES

Radiomics with artificial intelligence

Burak Koçak, Emine Şebnem Durmaz, Ece Ateş, Özgür Kılıçkesmez

Artificial intelligence in prostate cancer detection

Stephanie A. Harmon, Sena Tuncer, Thomas Sanford, Peter L. Choyke, Barış Türkbey

Predictors of post liver biopsy bleeding

Mehran Midia, Devang Odedra, Anatoly Shuster, Ramin Midia, Jeffrey Muir

Spectral detector computed tomography

Nils Große Hokamp, David Maintz, Nadav Shapira, De Hua Chang, Peter B Noël

Liver segmentation and volume determination using automatic vs. semi-automatic methods

A. Emre Kavur, Naciye Sinem Gezer, Mustafa Barış, Yusuf Şahin, Savaş Özkan, Bora Baydar, Ulaş Yüksel, Çağlar Kılıkçıer, Şahin Olut, Gözde Bozdağı Akar, Gözde Ünal, Oğuz Dicle, M. Alper Selver

High-intensity focused ultrasound

Nguyen Minh Duc, Bilgin Keserci

Differentiation of cytotoxic and vasogenic edema in a patient with reversible posterior leukoencephalopathy syndrome using diffusion-weighted MRI

By: Doelken, Marc; Lanz, Stefan; Rennert, Janine; et al.

Diagnosis and management of hemoptysis

By: Larici, Anna Rita; Franchi, Paola; Occhipinti, Mariaelena; et al.

Prostate cancer detection with MRI: is dynamic contrast-enhanced imaging necessary in addition to diffusion-weighted imaging?

By: Iwazawa, Jin; Mitani, Takashi; Sassa, Seitaro; et al.

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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A novel index to estimate the corpus callosum morphometry in adults: callosal/supratentorialsupracallosal area ratio

Nuri Erdoğan, Harun Ülger, İbrahim Tuna, Aylin Okur

(Diagn Interv Radiol 2005; 11: 179-181)

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Quantitative evaluation of ischemic myocardial scar tissue by unenhanced T1 mapping using 3.0 Tesla MR scanner

Aylin Okur, Mecit Kantarcı, Yeşim Kızrak, Sema Yıldız, Berhan Pirimoğlu, Leyla Karaca, Hayri Oğul, Serdar Sevimli

(Diagn Interv Radiol 2014; 20: 407-413) DOI: 10.5152/dir.2014.13520

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MRI of pneumonia in immunocompromised patients: comparison with CT

Afra Ekinci, Tuba Yücel Uçarkuş, Aylin Okur, Mehmet Öztürk, Serap Doğan

(Diagn Interv Radiol 2017; 23: 22-28) DOI: 10.5152/dir.2016.16055

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