Deep Learning-Based Assessment of Functional Liver Capacity Using Gadoxetic Acid-Enhanced Hepatobiliary Phase MRI-Reference-Cited by-同舟云学术

Deep Learning-Based Assessment of Functional Liver Capacity Using Gadoxetic Acid-Enhanced Hepatobiliary Phase MRI

Published:2022 Issue:7 Volume:23 Page:720
ISSN:1229-6929
Container-title:Korean Journal of Radiology
language:en
Short-container-title:Korean J Radiol

Author:

Park Hyo Jung¹^ORCID,Yoon Jee Seok²^ORCID,Lee Seung Soo¹^ORCID,Suk Heung-Il²³^ORCID,Park Bumwoo¹^ORCID,Sung Yu Sub¹^ORCID,Hong Seung Baek⁴^ORCID,Ryu Hwaseong⁵^ORCID

Affiliation:

1. Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.

2. Department of Brain and Cognitive Engineering, Korea University, Seoul, Korea.

3. Department of Artificial Intelligence, Korea University, Seoul, Korea.

4. Department of Radiology, Pusan National University Hospital, Busan, Korea.

5. Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Korea.

Funder

National Research Foundation of Korea

Publisher

The Korean Society of Radiology

Subject

Radiology, Nuclear Medicine and imaging

Link

https://kjronline.org/pdf/10.3348/kjr.2021.0892

Reference31 articles.

1. The value of residual liver volume as a predictor of hepatic dysfunction and infection after major liver resection

2. CT volumetry of the liver: Where does it stand in clinical practice?

3. The significance of measuring liver volume using computed tomographic images before and after hepatectomy

4. An ordinal model to predict the risk of symptomatic liver failure in patients with cirrhosis undergoing hepatectomy

5. Liver parenchymal enhancement of hepatocyte-phase images in Gd-EOB-DTPA-enhanced MR imaging: Which biological markers of the liver function affect the enhancement?

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