Emre Kayan, ve Tarık Kavuşan, Sevgi Önal, D. P. Okvur, ve Özden Y. Özuysal, B. U. Töreyin, D. Ünay
{"title":"从相衬显微镜图像序列分析细胞运动的初步研究","authors":"Emre Kayan, ve Tarık Kavuşan, Sevgi Önal, D. P. Okvur, ve Özden Y. Özuysal, B. U. Töreyin, D. Ünay","doi":"10.1109/TIPTEKNO50054.2020.9299319","DOIUrl":null,"url":null,"abstract":"Analyses of morphology, polarity, and motility of cells is important for cell biology research such as metastatic and invasive capacity of cells, wound healing, and embryonic development. Automation of such analyses using image series of phase-contrast optical microscopy, which allows label-free imaging of live cells in their living environment, is a need. With this purpose, in this study image series of a cell motility experiment is manually annotated, and an automation algorithm realizing motion and shape analyses of cells using the annotated data is developed. In addition, due to the low number of annotated data at hand, a U-Net based solution is devised for automated segmentation of the cells and its performance is evaluated.","PeriodicalId":426945,"journal":{"name":"2020 Medical Technologies Congress (TIPTEKNO)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Preliminary Study on Cell Motility Analysis from Phase-Contrast Microscopy Image Series\",\"authors\":\"Emre Kayan, ve Tarık Kavuşan, Sevgi Önal, D. P. Okvur, ve Özden Y. Özuysal, B. U. Töreyin, D. Ünay\",\"doi\":\"10.1109/TIPTEKNO50054.2020.9299319\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Analyses of morphology, polarity, and motility of cells is important for cell biology research such as metastatic and invasive capacity of cells, wound healing, and embryonic development. Automation of such analyses using image series of phase-contrast optical microscopy, which allows label-free imaging of live cells in their living environment, is a need. With this purpose, in this study image series of a cell motility experiment is manually annotated, and an automation algorithm realizing motion and shape analyses of cells using the annotated data is developed. In addition, due to the low number of annotated data at hand, a U-Net based solution is devised for automated segmentation of the cells and its performance is evaluated.\",\"PeriodicalId\":426945,\"journal\":{\"name\":\"2020 Medical Technologies Congress (TIPTEKNO)\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 Medical Technologies Congress (TIPTEKNO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TIPTEKNO50054.2020.9299319\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Medical Technologies Congress (TIPTEKNO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TIPTEKNO50054.2020.9299319","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Preliminary Study on Cell Motility Analysis from Phase-Contrast Microscopy Image Series
Analyses of morphology, polarity, and motility of cells is important for cell biology research such as metastatic and invasive capacity of cells, wound healing, and embryonic development. Automation of such analyses using image series of phase-contrast optical microscopy, which allows label-free imaging of live cells in their living environment, is a need. With this purpose, in this study image series of a cell motility experiment is manually annotated, and an automation algorithm realizing motion and shape analyses of cells using the annotated data is developed. In addition, due to the low number of annotated data at hand, a U-Net based solution is devised for automated segmentation of the cells and its performance is evaluated.