Adversarial attacks on deep learning models for fatty liver disease classification by modification of ultrasound image reconstruction method-Reference-Cited by-同舟云学术

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Adversarial attacks on deep learning models for fatty liver disease classification by modification of ultrasound image reconstruction method

Published:2020-09-07 Issue: Volume: Page:
ISSN:
Container-title:2020 IEEE International Ultrasonics Symposium (IUS)
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Author:

Byra Michal,Styczynski Grzegorz,Szmigielski Cezary,Kalinowski Piotr,Michalowski Lukasz,Paluszkiewicz Rafal,Ziarkiewicz-Wroblewska Bogna,Zieniewicz Krzysztof,Nowicki Andrzej

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9251288/9251278/09251568.pdf?arnumber=9251568

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Systematically Assessing the Security Risks of AI/ML-enabled Connected Healthcare Systems;2024 IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE);2024-06-19

2. Adversarial Attack and Defense Mechanisms in Medical Imaging: A Comprehensive Review;2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT);2024-02-09

3. Securing the Diagnosis of Medical Imaging: An In-depth Analysis of AI-Resistant Attacks;2024-02-07

4. Application of artificial intelligence techniques for non-alcoholic fatty liver disease diagnosis: A systematic review (2005–2023);Computer Methods and Programs in Biomedicine;2024-02

5. Adversarial Detection and Defense for Medical Ultrasound Images: From a Frequency Perspective;IFMBE Proceedings;2024

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