从大型自动化成像实验中提取具有生物医学重要性的信息。
EXTRACTING BIOMEDICALLY IMPORTANT INFORMATION FROM LARGE, AUTOMATED IMAGING EXPERIMENTS.
作者信息
Carpenter Anne E
机构信息
Imaging Platform, Broad Institute of Harvard and MIT.
出版信息
Proc IEEE Int Symp Biomed Imaging. 2011:1723-1726. doi: 10.1109/ISBI.2011.5872737.
Abstract
Major challenges remain in the extraction of rich information from high-throughput microscopy experiments. In this paper, I describe some of these challenges, particularly those that are the subject of ongoing research in my laboratory. The challenges include segmenting neurons, co-cultures of different cell types, and whole organisms; segmenting and tracking cells in time-lapse images; quantifying complex phenotypic changes; and discovering biologically relevant subpopulations of cells.
摘要
从高通量显微镜实验中提取丰富信息仍然面临重大挑战。在本文中，我描述了其中一些挑战，特别是那些我实验室正在进行研究的课题。这些挑战包括对神经元、不同细胞类型的共培养物以及整个生物体进行分割；在延时图像中对细胞进行分割和跟踪；量化复杂的表型变化；以及发现具有生物学相关性的细胞亚群。
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