Image-based Cell Phenotyping Using Deep Learning
Image-based Cell Phenotyping Using Deep Learning
Abstract The ability to phenotype cells is fundamentally important in biological research and medicine. Current methods rely primarily on fluorescence labeling of specific markers. However, there are many situations where this approach is unavailable or undesirable. Machine learning has been used for image cytometry but has been limited by cell agglomeration and it is unclear if this approach can reliably phenotype cells indistinguishable to the human eye. Here, we show disaggregated single cells can be phenotyped with a high degree of accuracy using low-resolution bright-field and non-specific fluorescence images of the nucleus, cytoplasm, and cytoskeleton. Specifically, we trained a convolutional neural network using automatically segmented images of cells from eight standard cancer cell-lines. These cells could be identified with an average classification accuracy of 94.6%, tested using separately acquired images. Our results demonstrate the potential to develop an “electronic eye” to phenotype cells directly from microscopy images indistinguishable to the human eye.
Matthews Kerryn、Duffy Simon P.、Berryman Samuel、Lee Jeong Hyun、Ma Hongshen
Department of Mechanical Engineering, University of British Columbia||Centre for Blood Research, University of British ColumbiaDepartment of Mechanical Engineering, University of British Columbia||Centre for Blood Research, University of British Columbia||British Columbia Institute of TechnologyDepartment of Mechanical Engineering, University of British Columbia||Centre for Blood Research, University of British ColumbiaDepartment of Mechanical Engineering, University of British Columbia||Centre for Blood Research, University of British ColumbiaDepartment of Mechanical Engineering, University of British Columbia||Centre for Blood Research, University of British Columbia||School of Biomedical Engineering, University of British Columbia||Department of Urologic Sciences, University of British Columbia
医学研究方法细胞生物学生物科学研究方法、生物科学研究技术
Deep-learningMicroscopyPhenotypeImage cytometry
Matthews Kerryn,Duffy Simon P.,Berryman Samuel,Lee Jeong Hyun,Ma Hongshen.Image-based Cell Phenotyping Using Deep Learning[EB/OL].(2025-03-28)[2025-05-02].https://www.biorxiv.org/content/10.1101/817544.点此复制
评论