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使用混合特征选择方法的高性能乳腺癌诊断方法.

Mohammad Moradi1, Abdalhossein Rezai2

  • 1ACECR Institute of Higher Education, Isfahan Branch, Isfahan, Iran.

Biomedizinische Technik. Biomedical engineering
|December 22, 2024
PubMed
概括

这项研究使用热成像和一种新的计算机辅助诊断 (CAD) 系统来加强乳腺癌诊断. 改进的CAD系统实现了高精度,有助于早期发现和治疗乳腺癌.

科学领域:

  • 生物医学工程 生物医学工程
  • 医疗成像医学成像
  • 人工智能在医学中的应用

背景情况:

  • 乳腺癌是妇女死亡的主要原因,使得早期和准确的诊断至关重要.
  • 计算机辅助诊断 (CAD) 系统为诊断过程中的临床医生提供了宝贵的支持.
  • 热成像为乳腺癌检测提供了一种非侵入性的方法.

研究的目的:

  • 为了提高乳腺癌诊断CAD系统的性能.
  • 开发一种有效的方法,以使用热图来改善乳腺癌诊断.

主要方法:

  • 在特征提取中采用了细分断层纹理分析 (SFTA) 算法.
  • 使用混合特征选择算法,结合二进制灰狼优化和火虫优化.
  • 应用kNN,SVM和DTree分类技术进行性能评估.

主要成果:

  • 提出的方法实现了高诊断性能指标.
  • 准确率:97%,特异性:96%,敏感性:98%,马修斯相关系数 (MCC):94.17%.

结论:

  • 开发的CAD系统与使用热图像诊断乳腺癌的现有方法相比,表现优越.
关键词:
计算机辅助诊断 (CAD) 系统系统乳腺癌 乳腺癌 乳腺癌功能提取 特性提取功能选择 功能选择热图学 热图学 热图学 热图学

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  • 拟议的方法为乳腺癌检测提供了一个高效和准确的工具.