Deep learning–based image reconstruction of 40-keV virtual monoenergetic images of dual-energy CT for the assessment of hypoenhancing hepatic metastasis-Reference-Cited by-同舟云学术

Deep learning–based image reconstruction of 40-keV virtual monoenergetic images of dual-energy CT for the assessment of hypoenhancing hepatic metastasis

Published:2022-04-05 Issue:9 Volume:32 Page:6407-6417
ISSN:1432-1084
Container-title:European Radiology
language:en
Short-container-title:Eur Radiol

Author:

Lee Taehee,Lee Jeong Min^ORCID,Yoon Jeong Hee,Joo Ijin,Bae Jae Seok,Yoo Jeongin,Kim Jae Hyun,Ahn Chulkyun,Kim Jong Hyo

Funder

The Ministry of Science and ICT, the Ministry of Trade, Industry and Energy, the Ministry of Health & Welfare, the Ministry of Food and Drug Safety

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s00330-022-08728-0.pdf

Reference43 articles.

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3. Sica GT, Ji H, Ros PR (2000) CT and MR imaging of hepatic metastases. AJR Am J Roentgenol 174:691–698

4. Granata V, Fusco R, de Lutio di Castelguidone E et al (2019) Diagnostic performance of gadoxetic acid-enhanced liver MRI versus multidetector CT in the assessment of colorectal liver metastases compared to hepatic resection. BMC Gastroenterol 19:129

5. Motosugi U, Ichikawa T, Morisaka H et al (2011) Detection of pancreatic carcinoma and liver metastases with gadoxetic acid-enhanced MR imaging: comparison with contrast-enhanced multi-detector row CT. Radiology 260:446–453

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