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EISSN 1305-3612

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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.

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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

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COVID-19 radiology CT personnel management

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

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

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Low-dose chest CT to diagnose COVID-19

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Quantitative chest CT in COVID-19

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Vascular changes in COVID-19 pneumonia

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

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MRI of diffuse liver disease: the common and uncommon etiologies

Surya Chundru, Bobby Kalb, Hina Arif-Tiwari, Puneet Sharma, James Costello, Diego R. Martin

(Diagn Interv Radiol 2013; 19: 479-487) DOI: 10.5152/dir.2013.13148

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Magnetic resonance enterography in Crohn's disease: techniques, interpretation, and utilization for clinical management

Diego R. Martin, Bobby Kalb, Cary G. Sauer, Adina Alazraki, Steve Goldschmid

(Diagn Interv Radiol 2012; 18: 374-386) DOI: 10.4261/1305-3825.DIR.4893-11.2

Abstract Full Text (PDF) Related Articles

Measurement of liver fat fraction and iron with MRI and MR spectroscopy techniques.

Puneet Sharma, Maria Altbach, Jean-Philippe Galons, Bobby Kalb, Diego R. Martin

(Diagn Interv Radiol 2014; 20: 17-26) DOI: 10.5152/dir.2013.13124

Abstract Full Text (PDF) Related Articles

MRI of diffuse liver disease: the common and uncommon etiologies

Magnetic resonance enterography in Crohn's disease: techniques, interpretation, and utilization for clinical management

Measurement of liver fat fraction and iron with MRI and MR spectroscopy techniques.

MRI of diffuse liver disease: characteristics of acute and chronic diseases

MRI of hepatocellular carcinoma: an update of current practices