Quantum optics and channel coding in imaging: advancements through deep learning

Liang Chen, Yue Xu,Hong Wen, Zhiwei Chen,Wenjing Hou

Optical and Quantum Electronics(2024)

引用 0|浏览1
暂无评分
摘要
In our relentless pursuit of improving healthcare and elevating wellness standards, we have unveiled a groundbreaking approach that amalgamates the cutting-edge realms of quantum optics, Channel coding, artificial intelligence (AI), and Advanced Optical Systems (optical IoT). This innovative collaboration is meticulously designed to fortify healthcare systems while enhancing cybersecurity protocols in the healthcare imaging sector. At the heart of this transformative initiative lies the cyber security threat and detecting analysis (CYSTDA), a groundbreaking framework that seamlessly integrates the strengths of AI, quantum optics, and advanced optical IoT to secure sensitive imaging data and systems. Quantum optics, known for its precision and sensitivity, offers a robust foundation for safeguarding imaging data. By leveraging quantum principles, it becomes possible to encode and protect visual information in an exceptionally secure manner. Channel coding techniques, initially designed for communication systems, are adapted to ensure the integrity and confidentiality of imaging data transmission, mitigating the risks of cyberattacks. On the other hand, AI plays a crucial role in CYSTDA by providing advanced threat detection techniques using deep learning models such as neural networks, enabling real-time monitoring and analysis of imaging data, and detecting anomalies and potential security breaches. This approach enhances the cybersecurity posture of imaging systems and safeguards the confidentiality of the visual information. Integration of advanced optical IoT is the other advantage of CYSTDA for improving cybersecurity in imaging; by deploying interconnected security devices and sensors, CYSTDA establishes a dynamic and secured ecosystem. Overall, the CYSTDA, which leverages the advanced technologies discussed earlier, was used to elevate cybersecurity protocols for imaging. This framework has the potential to significantly enhance the security of visual data, imaging devices, and infrastructure, safeguarding the confidentiality and integrity of imaging information in an increasingly digital and interconnected world.
更多
查看译文
关键词
Healthcare transformation,Cybersecurity,AI,IoT,Advanced optical systems,Anomaly detection,Channel coding,Healthcare imaging
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要