日本医学影像数据库(J-MID):支持数据科学的医疗大数据。

Juntendo medical journal Pub Date : 2025-06-04 eCollection Date: 2025-01-01 DOI:10.14789/ejmj.JMJ25-0004-P
Toshiaki Akashi, Kanako K Kumamaru, Akihiko Wada, Masahiro Hashimoto, Kenji Hirata, Yayoi Hayakawa, Katsuhiro Sano, Koji Kamagata, Akifumi Hagiwara, Yutaka Ikenouchi, Shigeki Aoki
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引用次数: 0

摘要

放射学实践的数字化已经发展了近二十年,以全球标准的医学数字成像和通信(DICOM)为例。成像方式的快速技术进步导致处理的数据量显著增加。然而,在日本,数量有限的放射科医生很难在有效处理数据的同时保持诊断质量。对此,日本放射学会(JRS)提出了“日本安全放射学”倡议,旨在通过在放射实践的各个方面积极利用信息和通信技术(ICT)来提高放射医学的安全性、效率和质量。创新人工智能(AI)技术的最新进展显示出对图像处理的高度亲和力,促使人们认识到使用大数据系统集成放射医学的重要性。因此,2017年,日本医学研究与开发机构(AMED)支持了JRS项目,即实现国家图像诊断数据库的开发研究,通过该项目建立了日本医学图像数据库(J-MID)。J-MID旨在通过学术信息网络(SINET)集中医疗资源,系统地收集日本10所主要大学医院的CT/MR图像和诊断报告。数据匿名存储在云端的中央服务器上,使研究人员能够方便地使用J-MID。到2024年4月,J-MID已经收集了超过5.34亿张图像(165万例),使其成为日本无与伦比的真实世界放射数据库。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Japan-Medical Image Database (J-MID): Medical Big Data Supporting Data Science.

The digitization of radiology practices has advanced for nearly two decades, exemplified by the global standard Digital Imaging and Communications in Medicine (DICOM). Rapid technological progress in imaging modalities has led to a significant increase in the volume of data handled. However, it has become difficult for the limited number of radiologists in Japan to maintain the quality of diagnosis while efficiently processing the data. In response, the Japan Radiological Society (JRS) advocated the "Japan Safe Radiology" Initiative, which aims to improve the safety, efficiency, and quality of radiological medicine by actively utilizing information and communication technology (ICT) in all aspects of radiological practice. Recent advances in innovative artificial intelligence (AI) technology have shown a high affinity for image processing, prompting recognition of the importance of using big data systems to integrate radiological medicine. Consequently, in 2017, the Japan Agency for Medical Research and Development (AMED) supported the JRS project, Development Research for the Realization of a National Image Diagnosis Database, through which the Japan Medical Image Database (J-MID) was established. The J-MID is designed to centralize medical resources and systematically collect CT/MR images and diagnostic reports from 10 major university hospitals in Japan through an academic information network (SINET). Data were anonymized and stored on a central server in the cloud, enabling researchers to utilize J-MID conveniently. In April 2024, J-MID had collected more than 534 million images (1.65 million cases), making it an unparalleled repository of real-world radiological data in Japan.

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