摘要
Journal of Magnetic Resonance ImagingEarly View Editorial Editorial for “A Multi-Modality Fusion Deep Learning Model Based on DCE-MRI for Preoperative Prediction of Microvascular Invasion in Intrahepatic Cholangiocarcinoma” Ponnada A. Narayana PhD, Corresponding Author Ponnada A. Narayana PhD ponnada.a.narayana@uth.tmc.edu orcid.org/0000-0002-5703-4346 Department of Diagnostic and Interventional Imaging, McGovern Medical School, University of Texas Health Science Center, Houston, Texas, 77401 USASearch for more papers by this authorRefaat E. Gabr PhD, Refaat E. Gabr PhD orcid.org/0000-0002-8802-3201 Department of Diagnostic and Interventional Imaging, McGovern Medical School, University of Texas Health Science Center, Houston, Texas, 77401 USASearch for more papers by this author Ponnada A. Narayana PhD, Corresponding Author Ponnada A. Narayana PhD ponnada.a.narayana@uth.tmc.edu orcid.org/0000-0002-5703-4346 Department of Diagnostic and Interventional Imaging, McGovern Medical School, University of Texas Health Science Center, Houston, Texas, 77401 USASearch for more papers by this authorRefaat E. Gabr PhD, Refaat E. Gabr PhD orcid.org/0000-0002-8802-3201 Department of Diagnostic and Interventional Imaging, McGovern Medical School, University of Texas Health Science Center, Houston, Texas, 77401 USASearch for more papers by this author First published: 21 February 2022 https://doi.org/10.1002/jmri.28124 Evidence Level:: 5 Technical Efficacy:: Stage 1 Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Early ViewOnline Version of Record before inclusion in an issue RelatedInformation