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The Potential Dangers of Artificial Intelligence for Radiology and Radiologists.

作者信息

Chu Linda C, Anandkumar Anima, Shin Hoo Chang, Fishman Elliot K

机构信息

The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.

Department of Computing and Mathematical Science, California Institute of Technology, Pasadena, California; NVIDIA Corporation, Santa Clara, California.

出版信息

J Am Coll Radiol. 2020 Oct;17(10):1309-1311. doi: 10.1016/j.jacr.2020.04.010. Epub 2020 Apr 17.

DOI:10.1016/j.jacr.2020.04.010
PMID:32360451
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7164850/
Abstract
摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62a2/7164850/c77748fbfc6c/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62a2/7164850/c77748fbfc6c/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62a2/7164850/c77748fbfc6c/gr1_lrg.jpg

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Creating Artificial Images for Radiology Applications Using Generative Adversarial Networks (GANs) - A Systematic Review.使用生成对抗网络 (GANs) 为放射学应用创建人工图像 - 系统评价。
Acad Radiol. 2020 Aug;27(8):1175-1185. doi: 10.1016/j.acra.2019.12.024. Epub 2020 Feb 5.
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DICOM Images Have Been Hacked! Now What?DICOM 图像被黑客攻击了！现在该怎么办？
AJR Am J Roentgenol. 2020 Apr;214(4):727-735. doi: 10.2214/AJR.19.21958. Epub 2019 Nov 26.
3
How Secure Is Your Radiology Department? Mapping Digital Radiology Adoption and Security Worldwide.
人工智能在腹部影像学中的临床应用综述
Diagnostics (Basel). 2023 Sep 8;13(18):2889. doi: 10.3390/diagnostics13182889.
4
Using a Visual Turing Test to Evaluate the Realism of Generative Adversarial Network (GAN)-Based Synthesized Myocardial Perfusion Images.使用视觉图灵测试评估基于生成对抗网络（GAN）的合成心肌灌注图像的逼真度。
Cureus. 2022 Oct 24;14(10):e30646. doi: 10.7759/cureus.30646. eCollection 2022 Oct.
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The evaluation of the reduction of radiation dose via deep learning-based reconstruction for cadaveric human lung CT images.基于深度学习的重建技术降低人体肺部 CT 图像辐射剂量的评估。
Sci Rep. 2022 Jul 20;12(1):12422. doi: 10.1038/s41598-022-16798-9.
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Applications of Generative Adversarial Networks (GANs) in Positron Emission Tomography (PET) imaging: A review.生成对抗网络 (GAN) 在正电子发射断层扫描 (PET) 成像中的应用：综述。
Eur J Nucl Med Mol Imaging. 2022 Sep;49(11):3717-3739. doi: 10.1007/s00259-022-05805-w. Epub 2022 Apr 22.
AJR Am J Roentgenol. 2016 Apr;206(4):797-804. doi: 10.2214/AJR.15.15283. Epub 2016 Mar 2.