基于VGG特征提取网络的CT图像的光束硬化人工物校正方法
Hong Zhang1,2, Zhaoguang Ma2, Da Kang2
1School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China.
Sensors (Basel, Switzerland)
|April 12, 2025
概括
本研究介绍了一种基于VGG16的方法,用于纠正工业计算机断层扫描 (ICT) 成像中的光束硬化器件. 该技术显著提高了航空航天部件检查的图像质量.
科学领域:
- 医疗成像医学成像
- 计算机视觉 计算机视觉
- 材料科学 材料科学 材料科学
背景情况:
- 在X射线工业计算机断层扫描 (ICT) 中的光束硬化器件降低了图像质量,影响了航空航天部件的缺陷检测.
- 效应,环形工件和相反分辨率降低是常见的问题,特别是高密度材料.
研究的目的:
- 开发和验证一种用于减轻ICT图像中的光束硬化工件的新方法.
- 提高关键航空航天应用的ICT成像的准确性和可靠性.
主要方法:
- 使用VGG16特征提取网络,自动识别和映射光束硬化工件.
- 创建了一组ICT图像数据集,以训练包含感知损失的卷积神经网络.
- 代训练优化了网络以抑制文物和恢复图像细节.
主要成果:
- 拟议的方法有效地抑制了器件,并减少了边缘模糊.
- 观察到显著提高图像对比度和减少图像噪声.
- 修复结构细节提高了ICT成像的整体可靠性.
结论:
- 基于VGG16的文物校正方法为改善航空航天领域的ICT图像质量提供了强大的解决方案.
- 这一进步支持在关键行业中更准确的缺陷检测和组件分析.
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