一种有效检索医疗图像的新方法:迈向计算机辅助诊断的一步
Suchita Sharma1, Ashutosh Aggarwal1
1Computer Science and Engineering Department, Thapar Institute of Engineering and Technology, Patiala 147004, Punjab, India.
Journal of imaging
|September 27, 2024
概括
这项研究引入了一种基于内容的医学图像检索系统,MsNrRiTxP,旨在用于计算机辅助诊断. 该系统在各种模式中展示了噪音和无噪音医疗图像的优异检索率.
科学领域:
- 医疗成像医学成像
- 计算机辅助诊断 计算机辅助诊断
- 生物医学工程 生物医学工程
背景情况:
- 医疗数据日益数字化,需要先进的信息检索方法.
- 基于内容的医学图像检索 (CBIR) 对于开发自动诊断系统至关重要.
- 随着COVID-19的爆发,医疗数据的有效分析变得更加重要.
研究的目的:
- 提出一个新的基于内容的医疗图像检索系统.
- 为了提取多分辨率,抗噪声和旋转不变的纹理特征.
- 提高计算机辅助诊断的准确性和效率.
主要方法:
- 将输入医疗图像转换为中微镜域,将其分解为三个中微镜图像.
- 在多个尺度上导出三个不同的模式描述器 (MsTrP,NrTxP,RiTxP).
- 通过联合直方图的尺度智能连接构建拟议的 MsNrRiTxP 模式描述器.
主要成果:
- 拟议的MsNrRiTxP描述符有效地提取多分辨率,抗噪声和旋转不变的纹理特征.
- 对CT和MRI数据集的实验结果显示,与现有方法相比,检索率要高得多.
- 该系统在无噪声和有噪声的医疗图像变体上都表现出强大的性能.
结论:
- 开发的基于 MsNrRiTxP 的 CBIR 系统在医疗图像检索方面取得了重大进展.
- 提出的方法显示了提高计算机辅助诊断质量的巨大潜力.
- 这种方法有助于在生物医学成像中开发更可靠的自动诊断工具.
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