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深度学习在计算机断层扫描中的作用。

Role of Deep Learning in Computed Tomography.

作者信息

Garg Yash, Seetharam Karthik, Sharma Manjari, Rohita Dipesh K, Nabi Waseem

机构信息

Internal Medicine, Wyckoff Heights Medical Center, New York, USA.

出版信息

Cureus. 2023 May 17;15(5):e39160. doi: 10.7759/cureus.39160. eCollection 2023 May.

Abstract

Computed tomography has played an instrumental role in the understanding of the pathophysiology of atherosclerosis in coronary artery disease. It enables visualization of the plaque obstruction and vessel stenosis in a comprehensive manner. As technology for computed tomography is constantly evolving, coronary applications and possibilities are constantly expanding. This influx of information can overwhelm a physician's ability to interpret information in this era of big data. Machine learning is a revolutionary approach that can help provide limitless pathways in patient management. Within these machine algorithms, deep learning has tremendous potential and can revolutionize computed tomography and cardiovascular imaging. In this review article, we highlight the role of deep learning in various aspects of computed tomography.

摘要

计算机断层扫描在理解冠状动脉疾病中动脉粥样硬化的病理生理学方面发挥了重要作用。它能够全面地显示斑块阻塞和血管狭窄情况。随着计算机断层扫描技术的不断发展,冠状动脉应用及可能性也在不断扩大。在这个大数据时代,这些信息的涌入可能会超出医生解读信息的能力。机器学习是一种革命性的方法,有助于在患者管理方面提供无限途径。在这些机器算法中,深度学习具有巨大潜力,能够彻底改变计算机断层扫描和心血管成像。在这篇综述文章中,我们重点介绍深度学习在计算机断层扫描各个方面的作用。

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