[人工智能在心血管放射学中的应用:图像采集、图像重建和工作流程优化]。

Radiologie (Heidelberg, Germany) Pub Date : 2024-10-01 Epub Date: 2024-06-24 DOI:10.1007/s00117-024-01335-8
Ann-Christin Klemenz, Mathias Manzke, Felix G Meinel
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引用次数: 0

摘要

背景:人工智能(AI)有可能从根本上改变放射学工作流程:人工智能(AI)有可能从根本上改变放射学工作流程:这篇综述文章概述了人工智能在心血管放射学中的应用,重点关注图像采集、图像重建和工作流程优化:首先,介绍人工智能在心血管计算机断层扫描(CT)和磁共振成像(MRI)中的成熟应用。在此基础上,我们介绍了目前正在开发和评估的一系列应用。我们对人工智能在心血管成像领域的实际优势、机遇和潜在风险进行了深入探讨。该报告基于相关专业文献以及我们自身的临床和科研经验:结果:基于人工智能的图像重建技术已经可以在市场上买到,它可以减少心血管 CT 的剂量,加速心脏 MRI 的图像采集。心血管 CT 和核磁共振成像检查的后处理已经可以利用成熟的人工智能分割算法大大简化。相比之下,许多针对心血管疾病诊断的人工智能应用的实际优势并不明显。此外,还应考虑到自动化偏差等潜在风险以及成本效益方面的考虑因素:在一个充满期望和技术快速发展的市场中,重要的是要实事求是地评估人工智能应用给自己的医院或诊所带来的实际效益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
[Artificial intelligence in cardiovascular radiology : Image acquisition, image reconstruction and workflow optimization].

Background: Artificial intelligence (AI) has the potential to fundamentally change radiology workflow.

Objectives: This review article provides an overview of AI applications in cardiovascular radiology with a focus on image acquisition, image reconstruction, and workflow optimization.

Materials and methods: First, established applications of AI are presented for cardiovascular computed tomography (CT) and magnetic resonance imaging (MRI). Building on this, we describe the range of applications that are currently being developed and evaluated. The practical benefits, opportunities, and potential risks of artificial intelligence in cardiovascular imaging are critically discussed. The presentation is based on the relevant specialist literature and our own clinical and scientific experience.

Results: AI-based techniques for image reconstruction are already commercially available and enable dose reduction in cardiovascular CT and accelerated image acquisition in cardiac MRI. Postprocessing of cardiovascular CT and MRI examinations can already be considerably simplified using established AI-based segmentation algorithms. In contrast, the practical benefits of many AI applications aimed at the diagnosis of cardiovascular diseases are less evident. Potential risks such as automation bias and considerations regarding cost efficiency should also be taken into account.

Conclusions: In a market characterized by great expectations and rapid technical development, it is important to realistically assess the practical benefits of AI applications for your own hospital or practice.

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