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在电子健康应用中使用深度神经网络进行安全的医疗图像传输

Ala Abdulsalam Alarood¹, Muhammad Faheem², Mahmoud Ahmad Al-Khasawneh³

¹College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia.

Healthcare technology letters

|August 2, 2023

概括

这项研究引入了一种用于医疗图像的新型加密方法,将深度神经网络与混乱系统相结合,以提高传输期间的数据安全性. 该技术有效地保护敏感的患者信息免受未经授权的访问.

科学领域:

医疗成像医学成像
网络安全网络安全
人工智能的人工智能

背景情况:

医学图像诊断至关重要,需要强大的数据传输安全性.
未经授权访问医疗图像存在重大风险.
加密,特别是混和扩散,对于保护图像数据至关重要.

研究的目的:

为医疗图像开发一个先进的加密算法.
提高医疗图像数据传输的安全性.
将深度神经网络与混乱系统集成,以改进加密.

主要方法:

调整了一个深度神经网络算法,以识别影响图像加密的关键权重.
使用来自深度神经网络的随机数字生成了一个混乱的系统.
感兴趣的图像区域被识别并使用深度神经网络进行处理,以进行像素再分配和混乱的系统集成.
使用了彩色和灰度医学图像.

主要成果:

提出的方法通过利用深度神经网络重量和混乱系统来证明有效的加密.
该算法成功生成了用于混乱系统创建的随机数字,包括行/列更换和像素分布.
评估和与现有方法的比较证实了拟议的算法的有效性和价值.

结论:

深度神经网络和混乱系统的集成为医疗图像加密提供了一个强大的方法.
该方法在网络传输期间为敏感医疗数据提供了增强的安全性.
这种技术解决了现代医疗保健中对安全医疗图像处理的关键需求.

关键词:

混乱的混乱的混乱的混乱混混混混混混混深度神经网络是一个神经网络.扩散扩散是一种扩散.进行加密,加密.随机性随机性随机性感兴趣的地区.

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