AI and computationally enhanced imaging with applications in bio-imaging

人工智能和计算增强成像及其在生物成像中的应用

• 批准号: 2279366
• 金额: --
• 依托单位: University of Glasgow
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2279366
• 关键词: AI; computationally; enhanced; imaging; applications

Aims of the researchOur project's primary goal is to create a high-resolution (million+ pixel) flourescence-lifetime imaging microscopy (FLIM) system. FLIM is a useful bio-imaging tool which can be used to map the locations and activities of proteins around cells. We aim to achieve real-time, wide field-of-view FLIM, to enable the imaging of cell-collective behaviour under external stimulation.Novelty/MethodThe project is a twofold endeavour, fusing hardware and software. My role in the project is to research and develop machine learning software to computationally improve the resolution of our physical imaging system. With machine learning, we aim to improve our resolution beyond what state-of-the-art instruments can measure under real-time conditions.Applications/contextUsing this system, we aim to advance biomedical studies in fields where cells behave in collective or bulk manners. Such fields include cancer-cell research and neural research.

研究目标我们项目的主要目标是创建一种高分辨率(百万像素以上)的荧光寿命成像显微镜(FLIM)系统。Flim是一种有用的生物成像工具，可以用来绘制细胞周围蛋白质的位置和活性。我们的目标是实现实时、宽视野的电影，以便能够在外部刺激下对细胞集体行为进行成像。我在这个项目中的角色是研究和开发机器学习软件，以通过计算提高我们物理成像系统的分辨率。通过机器学习，我们的目标是提高我们的分辨率，超出最先进的仪器在实时条件下可以测量的范围。应用/上下文使用这个系统，我们的目标是在细胞以集体或整体方式行为的领域推进生物医学研究。这些领域包括癌细胞研究和神经研究。