{"title":"未染色活果蝇细胞在显微镜下的识别","authors":"M. Tscherepanow, N. Jensen, F. Kummert","doi":"10.1109/IMVIP.2007.33","DOIUrl":null,"url":null,"abstract":"In order to localise tagged proteins in living cells, the surrounding cells must be recognised first. Based on previous work regarding cell recognition in bright-field images, we propose an approach to the automated recognition of unstained live Drosophila cells, which are of high biological relevance. In order to achieve this goal, the original methods were extended to enable the additional application of an alternative microscopy technique, since the exclusive usage of bright-field images does not allow for an accurate segmentation of the considered cells. In order to cope with the increased number of parameters to be set, a genetic algorithm is applied. Furthermore, the employed segmentation and classification techniques needed to be adapted to the new cell characteristics. Therefore, a modified active contour approach and an enhanced feature set, allowing for a more detailed description of the obtained segments, are introduced.","PeriodicalId":249544,"journal":{"name":"International Machine Vision and Image Processing Conference (IMVIP 2007)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Recognition of Unstained Live Drosophila Cells in Microscope Images\",\"authors\":\"M. Tscherepanow, N. Jensen, F. Kummert\",\"doi\":\"10.1109/IMVIP.2007.33\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to localise tagged proteins in living cells, the surrounding cells must be recognised first. Based on previous work regarding cell recognition in bright-field images, we propose an approach to the automated recognition of unstained live Drosophila cells, which are of high biological relevance. In order to achieve this goal, the original methods were extended to enable the additional application of an alternative microscopy technique, since the exclusive usage of bright-field images does not allow for an accurate segmentation of the considered cells. In order to cope with the increased number of parameters to be set, a genetic algorithm is applied. Furthermore, the employed segmentation and classification techniques needed to be adapted to the new cell characteristics. Therefore, a modified active contour approach and an enhanced feature set, allowing for a more detailed description of the obtained segments, are introduced.\",\"PeriodicalId\":249544,\"journal\":{\"name\":\"International Machine Vision and Image Processing Conference (IMVIP 2007)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Machine Vision and Image Processing Conference (IMVIP 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IMVIP.2007.33\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Machine Vision and Image Processing Conference (IMVIP 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMVIP.2007.33","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recognition of Unstained Live Drosophila Cells in Microscope Images
In order to localise tagged proteins in living cells, the surrounding cells must be recognised first. Based on previous work regarding cell recognition in bright-field images, we propose an approach to the automated recognition of unstained live Drosophila cells, which are of high biological relevance. In order to achieve this goal, the original methods were extended to enable the additional application of an alternative microscopy technique, since the exclusive usage of bright-field images does not allow for an accurate segmentation of the considered cells. In order to cope with the increased number of parameters to be set, a genetic algorithm is applied. Furthermore, the employed segmentation and classification techniques needed to be adapted to the new cell characteristics. Therefore, a modified active contour approach and an enhanced feature set, allowing for a more detailed description of the obtained segments, are introduced.