概括
我们开发了一种微型内镜,用于使用双波长全息技术进行精确的表面测量. 一种深度学习方法通过减少噪音阶段图中的测量误差,显著提高了准确性.
科学领域:
- 光学工程是指光学工程.
- 计量学 计量学 计量学
- 生物医学成像技术 生物医学成像技术
背景情况:
- 精确的微尺度表面地形测量对于各种科学和工业应用至关重要.
- 现有的微内镜技术由于光纤特性和噪声等因素而面临分辨率和精度的限制.
研究的目的:
- 提出一种新的微内镜地形测量方法,使用双波长全息.
- 评估光纤特性的影响,并引入虚拟表面粗度作为分辨率限制器.
- 开发和评估一个紧的微内镜系统,提高测量准确度.
主要方法:
- 在商业成像光纤束 (CFB) 中评估核心间分散和交叉通话.
- 使用3D打印的微光学设计和制造微内镜 (直径<450μm).
- 实施双波长全息以进行地形测量.
- 应用简单的阶段解封方法和深度学习方法来减少错误.
主要成果:
- 描述CFB属性和虚拟表面粗度的概念.
- 在金字塔测试对象上使用基本相解封方法实现了7.5%的相对测量误差.
- 使用深度学习方法来显著减少错误,该方法是针对噪音较大的相位图量身定制的.
- 通过深度学习方法,测量误差的标准偏差减少了4.2倍.
结论:
- 开发的微内镜系统可以在微尺度上进行准确的地形测量.
- 双波长全息相结合高级处理 (深度学习) 为高分辨率计量学提供了强大的解决方案.
- 深度学习方法有效地减轻噪音,提高微内镜测量的可靠性.
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