Machine learning in adaptive optics for improved biological imaging

自适应光学中的机器学习可改善生物成像

• 批准号: 2446091
• 金额: --
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2446091
• 关键词: Machine; learning; adaptive; optics; improved

Optical fibres, due to their thin shape, offer a powerful tool with which to acquire images of neurons within the delicate tissue of the brain while causing almost no mechanical damage. However, if optical fibre imaging is to be used in animals that are behaving normally current fibre techniques are not yet suitable as images cannot be formed should the fibre become bent.This project aims to develop a solution to allow imaging through an optical fibre as it bends, thereby allowing biologists to perform minimally disruptive optic fibre imaging in the brain of behaving animals.BBSRC priority areas addressed:Technology developments for the biosciences.

光纤由于其薄的形状，提供了一种强大的工具，可以在几乎不造成机械损伤的情况下获取大脑精细组织内神经元的图像。然而，如果要将光纤成像用于行为正常的动物，目前的光纤技术还不适合，因为如果光纤弯曲，就无法形成图像。该项目旨在开发一种解决方案，允许在光纤弯曲时通过光纤成像，从而使生物学家能够在行为正常的动物大脑中进行最小干扰的光纤成像。生物科学的技术发展。