Suppr超能文献

半个世纪的技术创新——为 21 世纪准备 MRI

A half-century of innovation in technology-preparing MRI for the 21st century.

机构信息

Philips Research, Hamburg, Germany.

Department of Radiology, LUMC, Leiden, the Netherlands.

出版信息

Br J Radiol. 2020 Jul;93(1111):20200113. doi: 10.1259/bjr.20200113. Epub 2020 Jun 15.

Abstract

MRI developed during the last half-century from a very basic concept to an indispensable non-ionising medical imaging technique that has found broad application in diagnostics, therapy control and far beyond. Due to its excellent soft-tissue contrast and the huge variety of accessible tissue- and physiological-parameters, MRI is often preferred to other existing modalities. In the course of its development, MRI underwent many substantial transformations. From the beginning, starting as a proof of concept, much effort was expended to develop the appropriate basic scanning technology and methodology, and to establish the many clinical contrasts (, , , flow, diffusion, water/fat, etc.) that MRI is famous for today. Beyond that, additional prominent innovations to the field have been parallel imaging and compressed sensing, leading to significant scanning time reductions, and the move towards higher static magnetic field strengths, which led to increased sensitivity and improved image quality. Improvements in workflow and the use of artificial intelligence are among many current trends seen in this field, paving the way for a broad use of MRI. The 125th anniversary of the BJR is a good point to reflect on all these changes and developments and to offer some slightly speculative ideas as to what the future may bring.

摘要

MRI 在过去的半个世纪里从一个非常基本的概念发展成为一种不可或缺的非电离医学成像技术,在诊断、治疗控制等方面得到了广泛的应用。由于其出色的软组织对比度和大量可获得的组织和生理参数,MRI 通常优于其他现有模态。在其发展过程中,MRI 经历了许多实质性的转变。从一开始,作为概念验证,就投入了大量精力来开发适当的基本扫描技术和方法,并建立了 MRI 今天著名的许多临床对比( , , ,流动,扩散,水/脂肪等)。除此之外,该领域的其他突出创新是并行成像和压缩感知,这导致扫描时间显著缩短,以及向更高的静态磁场强度发展,从而提高了灵敏度和图像质量。在这个领域,工作流程的改进和人工智能的使用是许多当前趋势之一,为 MRI 的广泛应用铺平了道路。BJR 创刊 125 周年之际,正是反思所有这些变化和发展并对未来可能带来的变化进行一些略具推测性的思考的好时机。

相似文献

2
MR Imaging in the 21st Century: Technical Innovation over the First Two Decades.21 世纪的磁共振成像:头二十年的技术创新。
Magn Reson Med Sci. 2022 Mar 1;21(1):71-82. doi: 10.2463/mrms.rev.2021-0011. Epub 2021 Apr 16.
5
Future directions in body magnetic resonance imaging.人体磁共振成像的未来发展方向。
Top Magn Reson Imaging. 2005 Feb;16(1):3-14. doi: 10.1097/01.rmr.0000180612.64338.41.
9
Water-Nanomaterial Interaction to Escalate Twin-Mode Magnetic Resonance Imaging.水与纳米材料的相互作用提升双模式磁共振成像
ACS Biomater Sci Eng. 2020 Aug 10;6(8):4377-4389. doi: 10.1021/acsbiomaterials.0c00409. Epub 2020 Jul 20.

引用本文的文献

2
Exploring scenarios for implementing fast quantitative MRI.探索实施快速定量磁共振成像的方案。
Eur J Radiol Open. 2025 May 8;14:100658. doi: 10.1016/j.ejro.2025.100658. eCollection 2025 Jun.
6
Will standardization kill innovation?标准化会扼杀创新吗?
MAGMA. 2023 Aug;36(4):525-528. doi: 10.1007/s10334-023-01115-w. Epub 2023 Aug 26.
9
Remote scanning support in magnetic resonance imaging: Friend or foe?磁共振成像中的远程扫描支持:是敌是友?
Radiography (Lond). 2022 Aug;28(3):739-745. doi: 10.1016/j.radi.2022.03.010. Epub 2022 Apr 9.
10
Infant and Child MRI: A Review of Scanning Procedures.婴幼儿磁共振成像:扫描程序综述
Front Neurosci. 2021 Jul 12;15:666020. doi: 10.3389/fnins.2021.666020. eCollection 2021.

本文引用的文献

5
k-Space deep learning for reference-free EPI ghost correction.k 空间深度学习用于无参考 EPI 鬼影校正。
Magn Reson Med. 2019 Dec;82(6):2299-2313. doi: 10.1002/mrm.27896. Epub 2019 Jul 18.
8
Low-field MRI: An MR physics perspective.低场 MRI:磁共振物理视角。
J Magn Reson Imaging. 2019 Jun;49(6):1528-1542. doi: 10.1002/jmri.26637. Epub 2019 Jan 13.
9
An overview of deep learning in medical imaging focusing on MRI.深度学习在医学影像中的概述,重点是 MRI。
Z Med Phys. 2019 May;29(2):102-127. doi: 10.1016/j.zemedi.2018.11.002. Epub 2018 Dec 13.
10
A Review of Denoising Medical Images Using Machine Learning 
Approaches.使用机器学习方法去噪医学图像的综述
Curr Med Imaging Rev. 2018 Oct;14(5):675-685. doi: 10.2174/1573405613666170428154156.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验