一个装有metaheuristics的冠状动脉血管图的后处理模型
K Y Devi1, J S Bobby2, S Vinurajkumar3
1Department of Biomedical Engineering, Easwari Engineering College, Ramapuram, Chennai, Tamil Nadu 600089, India.
Radiography (London, England : 1995)
|February 21, 2026
概括
这项研究引入了一种优化的对比限度自适应性基因图平衡 (CLAHE) 方法,用于增强冠状动脉血管图. 拟议的Optimum CLAHE (OCLAHE) 方法提高了图像质量,并有助于检测狭窄.
科学领域:
- 医疗成像医学成像
- 图像处理 图像处理
- 心血管诊断心血管诊断服务
背景情况:
- 与对比度有限的自适应组图平衡 (CLAHE) 增强了冠状动脉血管图.
- 优化剪切极限 (CL) 对于高质量,没有扭曲的CLAHE输出至关重要.
研究的目的:
- 在冠状动脉血管图增强中为CLAHE自动化剪切极限 (CL) 选择.
- 评估优化CLAHE (OCLAHE) 与现有方法的性能.
主要方法:
- 开发了一个参数优化模型,集成灰狼优化 (GWO) 和基于补丁的对比质量指数 (PCQI) 健身功能.
- 将OCLAHE与历史图平衡 (HE),不清晰的掩饰 (USM),形态过 (MF) 和弗兰吉过器 (FF) 进行比较.
- 使用主观视觉吸引力和客观图像质量评估 (IQA) 指数评估图像质量:PCQI,质量意识相对对比度 (QRCM),和盲人/无引用图像空间质量评估器 (BRISQUE).
主要成果:
- 与HE,USM,MF和FF相比,OCLAHE在所有客观IQA指数中表现优异.
- 奥克莱获得了更高的PCQI,QRCM和值.
- 在OCLAHE的结果中,BRISQUE得分较低,这表明视觉质量有所提高.
结论:
- 奥克拉赫保持了梯度配置和纹理完整性 (高QRCM),保持了高信息含量和对比度 (高),并呈现出自然的外观 (低BRISQUE).
- OCLAHE有效地放大了容器和背景之间的强度差异,而不会过度放大整体亮度.
- 来自OCLAHE的增强视觉质量有助于在冠状动脉血管图中自动和主观检测狭窄.
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