计算
显微镜
计算机科学
活体细胞成像
光学(聚焦)
荧光显微镜
分辨率(逻辑)
显微镜
图像分辨率
人工智能
计算机视觉
荧光
算法
细胞
光学
物理
化学
生物化学
作者
Hari Shroff,Ilaria Testa,Florian Jug,Suliana Manley
出处
期刊:Cornell University - arXiv
日期:2024-01-01
标识
DOI:10.48550/arxiv.2401.01438
摘要
The proliferation of microscopy methods for live-cell imaging offers many new possibilities for users but can also be challenging to navigate. We focus here on computational methods that promise to boost live-cell fluorescence microscopy, where intra-cellular dynamics and cell viability constrain measurements considerably. Considering the tradeoffs between signal-to-noise ratio (SNR), spatial resolution, temporal resolution, and multi-color and multi-channel capacity, we review computational methods that can be layered on top of commonly used existing microscopies, as well as hybrid methods that integrate computation and microscope hardware.
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