![Loading...](https://link.springer.com/static/c4a417b97a76cc2980e3c25e2271af3129e08bbe/images/pdf-preview/spacer.gif)
-
Article
Liver imaging: it is time to adopt standardized terminology
Liver imaging plays a vital role in the management of patients at risk for hepatocellular carcinoma (HCC); however, progress in the field is challenged by nonuniform and inconsistent terminology in the publish...
-
Article
Deep convolutional neural network applied to the liver imaging reporting and data system (LI-RADS) version 2014 category classification: a pilot study
To develop a deep convolutional neural network (CNN) model to categorize multiphase CT and MRI liver observations using the liver imaging reporting and data system (LI-RADS) (version 2014).
-
Article
LI-RADS® algorithm: CT and MRI
The Liver Imaging Reporting and Data System (LI-RADS®) is an imaging-based diagnostic system applicable in patients at high risk of hepatocellular carcinoma (HCC). In LI-RADS, each liver observation is assigned a...
-
Article
Hepatocarcinogenesis and LI-RADS
Hepatocarcinogenesis is a multi-step process characterized by progressive cellular and molecular dedifferentiation of hepatocytes and culminating in the emergence of hepatocellular carcinoma (HCC). Knowledge o...
-
Article
Comparative 13-year meta-analysis of the sensitivity and positive predictive value of ultrasound, CT, and MRI for detecting hepatocellular carcinoma
To compare the per-lesion sensitivity and positive predictive value (PPV) of ultrasonography (US), computed tomography (CT), and magnetic resonance imaging (MRI) for the diagnosis of hepatocellular carcinoma (...