深度学习在新冠肺炎患者肺部超声成像中的应用综述

IF 5 Q1 ENGINEERING, BIOMEDICAL
Lingyi Zhao, Muyinatu A Lediju Bell
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引用次数: 18

摘要

COVID-19的大规模持续传播促使世界各地的研究人员积极探索、了解和开发新的诊断和治疗技术。尽管与x射线和CT等其他医学成像方式相比,肺部超声成像是一种不太成熟的方法,但多项研究表明,它有望诊断COVID-19患者。同时,建立了许多深度学习模型来提高医学成像的诊断效率。这些最初平行的努力的整合导致多名研究人员报告了深度学习在COVID-19患者医学成像中的应用,其中大多数显示了深度学习在帮助COVID-19诊断方面的杰出潜力。这篇特邀综述的重点是深度学习在COVID-19肺部超声成像中的应用,并全面概述了用于数据采集、相关数据集、深度学习模型和比较性能的超声系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Review of Deep Learning Applications in Lung Ultrasound Imaging of COVID-19 Patients.

The massive and continuous spread of COVID-19 has motivated researchers around the world to intensely explore, understand, and develop new techniques for diagnosis and treatment. Although lung ultrasound imaging is a less established approach when compared to other medical imaging modalities such as X-ray and CT, multiple studies have demonstrated its promise to diagnose COVID-19 patients. At the same time, many deep learning models have been built to improve the diagnostic efficiency of medical imaging. The integration of these initially parallel efforts has led multiple researchers to report deep learning applications in medical imaging of COVID-19 patients, most of which demonstrate the outstanding potential of deep learning to aid in the diagnosis of COVID-19. This invited review is focused on deep learning applications in lung ultrasound imaging of COVID-19 and provides a comprehensive overview of ultrasound systems utilized for data acquisition, associated datasets, deep learning models, and comparative performance.

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