Pattern recognition and classification of two cancer cell lines by diffraction imaging at multiple pixel distances
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- 作者：He WangaAuthor Vitae ; Yuanming FengaAuthor Vitae ; Yu SaaAuthor Vitae ; Jun Q. LubAuthor Vitae ; Junhua DingcAuthor Vitae ; Jun ZhangaAuthor Vitae ; Xin-Hua Hub ; hux@ecu.edu" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae
- 关键词：Single-cell assay ; Image pattern analysis ; Diffraction imaging ; Cell classification ; Light scattering ; Flow cytometry ; Cancer cells
- 刊名：Pattern Recognition
- 出版年：2017
- 出版时间：January 2017
- 年：2017
- 卷：61
- 期：Complete
- 页码：234-244
- 全文大小：2665 K
文摘
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Cross-polarized diffraction images allow label-free cell classification.
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GLCM yields accurate and effective features for automated classification by SVM.
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Consistent accuracies are up to 99.8% on training and up to 99.5% on 3 test sets.
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Effects of image blur on classification have been quantitatively analyzed.
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Results indicate diffraction imaging flow cytometry as a powerful cell assay tool.