Lilla Élo, Róbert Paulik, G. Kiszler, T. Micsik, Tamás Székely, H. Hajdú, M. Kozlovszky, B. Molnár
{"title":"自动tma核心检测算法","authors":"Lilla Élo, Róbert Paulik, G. Kiszler, T. Micsik, Tamás Székely, H. Hajdú, M. Kozlovszky, B. Molnár","doi":"10.1109/IWOBI47054.2019.9114446","DOIUrl":null,"url":null,"abstract":"Tissue microarray (TMA) is a high-throughput technology for the analysis of molecular markers in oncology. This method supports the presentation of several different tissue samples -TMA cores- in one singe glass slide. However, because of the large size of TMA cores, the “identification and analysis” procedure is a more or less time-consuming method. The TMA core-finding algorithm detailed in this study detects each of the TMA cores on the slide and it creates outline annotation around the cores automatically. A validation study is also presented, through which detection accuracy of this algorithm for detecting cores on brightfield and fluorescent slides have been measured. We have found a 77.5% detection accuracy in average, so based on this result we can conclude that our TMA core detection solution can be utilized as a useful tool for supporting TMA analysis.","PeriodicalId":427695,"journal":{"name":"2019 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Automated TMA-Core-Detection Algorithm\",\"authors\":\"Lilla Élo, Róbert Paulik, G. Kiszler, T. Micsik, Tamás Székely, H. Hajdú, M. Kozlovszky, B. Molnár\",\"doi\":\"10.1109/IWOBI47054.2019.9114446\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Tissue microarray (TMA) is a high-throughput technology for the analysis of molecular markers in oncology. This method supports the presentation of several different tissue samples -TMA cores- in one singe glass slide. However, because of the large size of TMA cores, the “identification and analysis” procedure is a more or less time-consuming method. The TMA core-finding algorithm detailed in this study detects each of the TMA cores on the slide and it creates outline annotation around the cores automatically. A validation study is also presented, through which detection accuracy of this algorithm for detecting cores on brightfield and fluorescent slides have been measured. We have found a 77.5% detection accuracy in average, so based on this result we can conclude that our TMA core detection solution can be utilized as a useful tool for supporting TMA analysis.\",\"PeriodicalId\":427695,\"journal\":{\"name\":\"2019 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)\",\"volume\":\"150 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWOBI47054.2019.9114446\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWOBI47054.2019.9114446","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Tissue microarray (TMA) is a high-throughput technology for the analysis of molecular markers in oncology. This method supports the presentation of several different tissue samples -TMA cores- in one singe glass slide. However, because of the large size of TMA cores, the “identification and analysis” procedure is a more or less time-consuming method. The TMA core-finding algorithm detailed in this study detects each of the TMA cores on the slide and it creates outline annotation around the cores automatically. A validation study is also presented, through which detection accuracy of this algorithm for detecting cores on brightfield and fluorescent slides have been measured. We have found a 77.5% detection accuracy in average, so based on this result we can conclude that our TMA core detection solution can be utilized as a useful tool for supporting TMA analysis.