An overview of ultrasound-derived radiomics and deep learning in liver
-
Published:2023-12-27
Issue:4
Volume:25
Page:445
-
ISSN:2066-8643
-
Container-title:Medical Ultrasonography
-
language:
-
Short-container-title:Med Ultrason
Author:
Zhang Di,Zhang Xian-Ya,Duan Ya-Yang,Dietrich Christoph F,Cui Xin-Wu,Zhang Chao-Xue
Abstract
Over the past few years, developments in artificial intelligence (AI), especially in radiomics and deep learning, have enabled the extraction of pathophysiology-related information from varied medical imaging and are progressively transforming medical practice. AI applications are extending into domains previously thought to be accessible only to human experts. Recent research has demonstrated that ultrasound-derived radiomics and deep learning represent an enticing opportunity to benefit preoperative evaluation and prognostic monitoring of diffuse and focal liver disease. This review summarizes the application of radiomics and deep learning in ultrasound liver imaging, including identifying focal liver lesions and staging of liver fibrosis, as well as the evaluation of pathobiological properties of malignant tumors and the assessment of recurrence and prognosis. Besides, we identify important hurdles that must be overcome while also discussing the challenges and opportunities of radiomics and deep learning in clinical applications.
Publisher
SRUMB - Romanian Society for Ultrasonography in Medicine and Biology
Subject
Acoustics and Ultrasonics,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献