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Computed Tomography01:10

Computed Tomography

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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
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Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

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DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
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Updated: Apr 30, 2026

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery
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使用模块化集成物流指数地图和多层次Q序矩阵的新医疗图像加密

Abdelmajid H Mansour1, Sherihan Aboelenin2, Mohamed Meselhy Eltoukhy2

  • 1Department of Information Technology, College of Computing and Information Technology - Khulais, University of Jeddah, Jeddah, Saudi Arabia. emam@uj.edu.sa.

Scientific reports
|August 26, 2025
PubMed
概括

这项研究引入了一种新的医疗图像加密算法, 增强了数据安全性和隐私. 该方法使用改进后勤指数 (MILE) 混乱地图和多层次的斐波纳契Q矩阵,以在医疗保健中提供强大的保护.

关键词:
混乱的彩色医疗图像图像的加密进行加密指数地图菲博纳奇后勤地图一个小时编码的图像块

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科学领域:

  • 医疗成像安全
  • 密码学
  • 医疗保健中的信息技术

背景情况:

  • 医疗图像的保密性对于医疗保健中的患者隐私和数据完整性至关重要.
  • 现有的加密方法可能面临安全性,效率或对先进攻击的弹性方面的限制.

研究的目的:

  • 为灰度和彩色医疗图像开发创新和高效的加密算法.
  • 在存储和传输过程中增强医疗图像数据的安全性,随机性和弹性.

主要方法:

  • 拟议的算法结合了改进后勤指数 (MILE) 混乱地图与多层次的斐波那契Q矩阵.
  • 它采用关键依赖参数提取,混沌序列生成和基于XOR的扩散,以及多层次的Q矩阵转换.
  • 该方法解决了1D混乱系统的局限性,以提高不可预测性.

主要成果:

  • 该加密方案表现出强大的NPCR (99.63%) 和UACI (33.47%) 值.
  • 值接近理想的7.999,表明出色的随机性和对统计攻击的抵抗力.
  • 这个算法在计算上很高效, 能够在0.42秒内加密256x256的图像.

结论:

  • 拟议的加密算法为敏感的医疗数据提供了强大的保护.
  • 它的效率和强大的安全特性使其适合实时应用和远程医疗.
  • 这种方法优于现有的医疗图像加密技术.