Pattern recognition and classification of two cancer cell lines by diffraction imaging at multiple pixel distances
作者：
Highlights：
• Cross-polarized diffraction images allow label-free cell classification.
• GLCM yields accurate and effective features for automated classification by SVM.
• Consistent accuracies are up to 99.8% on training and up to 99.5% on 3 test sets.
• Effects of image blur on classification have been quantitatively analyzed.
• Results indicate diffraction imaging flow cytometry as a powerful cell assay tool.
摘要
•Cross-polarized diffraction images allow label-free cell classification.•GLCM yields accurate and effective features for automated classification by SVM.•Consistent accuracies are up to 99.8% on training and up to 99.5% on 3 test sets.•Effects of image blur on classification have been quantitatively analyzed.•Results indicate diffraction imaging flow cytometry as a powerful cell assay tool.
论文关键词：Single-cell assay,Image pattern analysis,Diffraction imaging,Cell classification,Light scattering,Flow cytometry,Cancer cells
论文评审过程：Received 9 February 2016, Revised 23 May 2016, Accepted 22 July 2016, Available online 25 July 2016, Version of Record 10 August 2016.
论文官网地址：https://doi.org/10.1016/j.patcog.2016.07.035
