Bioimage Analysis and Cell Motility

被引:19
作者
Boquet-Pujadas, Aleix [1 ,2 ,3 ]
Olivo-Marin, Jean-Christophe [1 ,2 ]
Guillen, Nancy [1 ,4 ]
机构
[1] Inst Pasteur, Bioimage Anal Unit, 25 Rue Dr Roux, F-75724 Paris 15, France
[2] CNRS, CNRS UMR3691, Paris, France
[3] Sorbonne Univ, F-75005 Paris, France
[4] CNRS, CNRS ERL9195, Paris, France
来源
PATTERNS | 2021年 / 2卷 / 01期
基金
欧盟地平线“2020”;
关键词
ENTAMOEBA-HISTOLYTICA; ACCURATE RECONSTRUCTION; FLUORESCENCE MICROSCOPY; PARTICLE TRACKING; IMAGE DATA; MYOSIN-II; CYTOSKELETON; MIGRATION; FORCES; SHAPE;
D O I
10.1016/j.patter.2020.100170
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Bioimage analysis (BIA) has historically helped study how and why cells move; biological experiments evolved in intimate feedback with the most classical image processing techniques because they contribute objectivity and reproducibility to an eminently qualitative science. Cell segmentation, tracking, and morphology descriptors are all discussed here. Using ameboid motility as a case study, these methods help us illustrate how proper quantification can augment biological data, for example, by choosing mathematical representations that amplify initially subtle differences, by statistically uncovering general laws or by integrating physical insight. More recently, the non-invasive nature of quantitative imaging is fertilizing two blooming fields: mechanobiology, where many biophysical measurements remain inaccessible, and microenvironments, where the quest for physiological relevance has exploded data size. From relief to remedy, this trend indicates that BIA is to become a main vector of biological discovery as human visual analysis struggles against ever more complex data.
引用
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页数:16
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