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Advances in artificial intelligence techniques drive the application of radiomics in the clinical research of hepatocellular carcinoma

查看全文 作　　者：Jingwei [1,2]Wei;Meng [3]Niu;Ouyang [4]Yabo;Yu [1,2,5]Zhou;Xiaoke [6]Ma;Xue [7]Yang;Hanyu [8]Jiang;Hui [1,2]Hui;Hongyi [9]Cao;Binwei [10]Duan;Hongjun [7,11]Li;Dawei [12]Ding;Jie [1,2,13,14]Tian 高影响力作者 机构地区：[1]Key Laboratory of Molecular Imaging,Institute of Automation,Chinese Academy of Sciences,Beijing 100190,China;[2]Beijing Key Laboratory of Molecular Imaging,Beijing 100190,China;[3]Department of Interventional Radiology,The First Affiliated Hospital of China Medical University,Shenyang,Liaoning,110000,China;[4]Beijing YouAn Hospital,Capital Medical University,Beijing Institute of Hepatology,Beijing,100069,China;[5]School of Life Science and Technology,Xidian University,Xi'an,China;[6]School of Computer Science and Technology,Xidian University,Xi'an,Shaanxi,China;[7]Department of Radiology,Beijing Youan Hospital,Capital Medical Universtiy,Beijing,100069,China;[8]Department of Radiology,West China Hospital,Sichuan University,Chengdu,Sichuan 610041,China;[9]Department of Pathology,College of Basic Medical Science,China Medical University,Shenyang,Liaoning,110000,China;[10]The Department of General Surgery Center,Beijing YouAn Hospital,Capital Medical University,China;[11]School of Bioengineering,Beihang University,Beijing,100191,China;[12]School of Automation and Electrical Engineering,University of Science and Technology Beijing,Beijing 100083,China;[13]Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of Medicine,Beihang University,Beijing,100191,China;[14]Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education,School of Life Science and Technology,Xidian University,Xi'an,Shaanxi,710126,China高影响力机构 出　　处：《iLIVER》索引2022年第1卷第1期,共6页高影响力期刊 基　　金：This study has received funding by the National Key Research and Development Program of China under Grant 2017YFA0700401 and 2021YFC2500402;Ministry of Science and Technology of China under Grant No.2017YFA0205200;National Natural Science Foundation of China under Grant No.82001917,81930053,82090052,82090051,82093219055,81227901,92159202 and 81527805;Beijing Natural Science Foundation under Grant No.L192061;the Project of High-Level Talents Team Introduction in Zhuhai City。 摘　　要：Hepatocellular carcinoma(HCC)remains the most common malignancy to threaten public health globally.With advances in artificial intelligence techniques,radiomics for HCC management provides a novel perspective to solve unmet needs in clinical settings,and reveals pixel-level radiological information for medical imaging big data,correlating the radiological phenotype with targeted clinical issues.Conventional radiomics pipelines depend on handcrafted engineering features,and further deep learning-based radiomics pipelines are supplemented with deep features calculated via self-learning strategies.During the past decade,radiomics has been widely applied in accurate diagnoses and pathological or biological behavior evaluation,as well as in prognosis prediction.In this review,we systematically introduce the main pipelines of artificial intelligence-based radiomics and their efficacy in the clinical studies of HCC. 关 键 词：Artificial intelligence DIAGNOSIS Hepatocellular carcinoma PROGNOSIS Radiomics
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