Xiao Yi, Liu Shi-Yuan
Department of Radiology, Changzheng Hospital, Naval Medical University (Second Military Medical University), Shanghai 200003, China.
Chin Med Sci J. 2019 Jun 30;34(2):84-88. doi: 10.24920/003619.
In recent years, artificial intelligence (AI) has developed rapidly in the field of medical imaging. However, the collaborations among hospitals, research institutes and enterprises are insufficient at the present, and there are various issues in technological transformation and value landing of products in this area. To solve the core problems in the developmental path of medical imaging AI, the Chinese Innovative Alliance of Industry, Education, Research and Application of Artificial Intelligence for Medical Imaging compiled the . This article introduces the current status of collaboration, the clinical demands for medical imaging AI technique, and the key points in AI technology transformation: robustness, usability and security. We are facing challenges of lacking industry standards, data desensitization standard, assessment system, as well as corresponding regulations and policies to realize the application values of AI products in medical imaging. Further development of AI in medical imaging requires breakthroughs of the core algorithm, deep involvement of doctors, input from capitals, patience from societies, and most importantly, the resolutions from government for multiple difficulties in links of landing the technology.
近年来，人工智能（AI）在医学成像领域发展迅速。然而，目前医院、科研机构和企业之间的合作不足，该领域产品的技术转化和价值落地存在诸多问题。为解决医学成像AI发展路径中的核心问题，中国医学影像人工智能产学研用创新联盟编撰了此文。本文介绍了合作现状、医学成像AI技术的临床需求以及AI技术转化的要点：鲁棒性、可用性和安全性。我们面临着缺乏行业标准、数据脱敏标准、评估体系以及相应法规政策等挑战，以实现AI产品在医学成像中的应用价值。医学成像AI的进一步发展需要核心算法的突破、医生的深度参与、资本的投入、社会的耐心，最重要的是政府解决技术落地环节中多重困难的决心。
