适应性光学校正用于体内双光子光显微镜与神经场的体内双光子光显微镜
bioRxiv : the preprint server for biology
|November 1, 2024
概括
NeAT是一种适应光学显微镜的新计算框架,它可以在不需要训练数据的情况下纠正光学偏差和样本运动. 这使得活生生的小鼠大脑能够在体内更清晰地成像.
科学领域:
- 神经科学是一个神经科学.
- 生物物理学的生物物理.
- 显微镜的使用方法
背景情况:
- 适应光学 (AO) 为改进的显微镜校正光学偏差,但通常需要自定义设置,并且对样品运动敏感.
- 现有的AO系统可能很复杂,在商业显微镜或在生物样本运动的存在下,可能无法达到最佳性能.
研究的目的:
- 介绍NeAT,一个适应光学计算框架,用于双光子光显微镜.
- 开发一种不需要外部训练数据集的偏差校正和样本结构恢复方法.
- 为了实现实时,生物实验室的体内成像,包括商业显微镜.
主要方法:
- NeAT利用神经场来估计波面偏差,并从图像堆中重建3D样本结构.
- 该框架包含了运动校正,并纠正了商业显微镜特有的结合错误.
- 使用定制制造和商用显微镜在各种偏差和运动条件下验证了性能.
主要成果:
- 在没有先前培训数据的情况下,NeAT成功估计了异常,并恢复了样本结构.
- 该系统使用商业显微镜在体内实时证明有效的偏差校正.
- 在活着的小鼠大脑中,NeAT显著改善了对谷氨酸和成像的信号和准确性.
结论:
- NeAT为适应光学显微镜提供了一种通用和可部署的计算解决方案.
- 该框架通过解决异常和运动器件来增强体内成像能力.
- NeAT提高了神经科学研究中的功能和形态成像的质量和可靠性.
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