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EDITORIAL article

Front. Med.
Sec. Nuclear Medicine
Volume 11 - 2024 | doi: 10.3389/fmed.2024.1487230
This article is part of the Research Topic Workflow Optimisation for Radiological Imaging View all 17 articles

Editorial: Workflow Optimisation for Radiological Imaging

Provisionally accepted
Jie-Zhi Cheng Jie-Zhi Cheng 1*Minjeong Kim Minjeong Kim 2Xin Yang Xin Yang 3
  • 1 Shanghai United Imaging Intelligence, Co., Ltd., Shanghai, China
  • 2 University of North Carolina at Greensboro, Greensboro, North Carolina, United States
  • 3 Huazhong University of Science and Technology, Wuhan, Hubei Province, China

The final, formatted version of the article will be published soon.

    Keywords: artificial intelligence, Radiological imaging, computer-aided diagnosis, Cancer staging, Metastasis prediction, quantitative 2 analysis, Prognosis prediction

    Received: 27 Aug 2024; Accepted: 30 Aug 2024.

    Copyright: © 2024 Cheng, Kim and Yang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Jie-Zhi Cheng, Shanghai United Imaging Intelligence, Co., Ltd., Shanghai, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.