Abstract
Dual-energy computed tomography (DECT) applies two energy spectra distributions to collect raw data based on traditional CT imaging. The application of hepatobiliary imaging, has the advantages of optimizing the scanning scheme, improving the imaging quality, highlighting the disease characterization, and increasing the detection rate of lesions. In order to summarize the clinical application value of DECT in hepatobiliary diseases, we searched the technical principles of DECT and its existing studies, case reports, and clinical guidelines in hepatobiliary imaging from 2010 to 2023 (especially in the past 5 years) through PubMed and CNKI, focusing on the clinical application of DECT in hepatobiliary diseases, including liver tumors, diffuse liver lesions, and biliary system lesions. The first part of this article briefly describes the basic concept and technical advantages of DECT. The following will be reviewed:the detection of lesions, diagnosis and differential diagnosis of lesions, hepatic steatosis, quantitative analysis of liver iron, and analyze the advantages and disadvantages of DECT in hepatobiliary imaging. Finally, the contents of this paper are summarized and the development prospect of DECT in hepatobiliary imaging is prospected.
Keywords: Computed tomography, Dual-energy CT, Imaging, Hepatobiliary diseases, Clinical value, Liver diseases.
Call for Papers in Thematic Issues
Deep Learning Approaches for Image Enhancement in Medical Diagnostics
The medical and healthcare sectors are very different from one another. Consumers in these sectors need more affordable, superior offerings. Health or medical specialists are typically the ones who analyse medical data. In particular, medical imaging evaluation heavily relies on machine learning and deep learning. They not only yield outstanding ...read more
Deep Learning for Advanced Image Analysis in Health Informatics
The field of health informatics has endured a sharp increase in the use of image analysis due to the abundance of versatile data. This has also led to a rise in fascination with the development of computational models based on information and deep learning in the field of health informatics. ...read more
Emerging Biomedical Imaging Informatic for Smart Healthcare
Biomedical imaging informatics is a field that deals with the acquisition, processing, and interpretation of images in biomedicine using computational approaches. Biomedical imaging has progressed from early, simple X-rays for fracture diagnosis and foreign body identification to various techniques used to research biological structure and function and answer fundamental biomedical ...read more
Emerging Trends & Techniques in Medical Imaging using Machine Learning and Deep Learning Techniques
This special issue will aim to discuss different approaches, initiatives and applications in Medical Imaging fields (including Machine Intelligence, Mining Engineering, Modeling and Simulation, Computer, Communication, Networking and Information Engineering, Systems Engineering, Innovative Computing Systems, Adaptive Technologies for Sustainable Growth, and Theoretical and Applied Sciences). This collection should inspire various ...read more
19