{"title":"[通过自动细胞分析(Fazytan系统)进行早期癌症诊断]。","authors":"E R Reinhardt, R Erhardt","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>A prescreening system for the early detection of uterine cancer was developed. For the diagnosis of each input specimen (PAP-stained), a figure of malignancy has to be calculated automatically. Methods, problems and results of the system are summarized in this paper. Some thousand microscopic subfields of a specimen are successively scanned by an optimized TV-camera with high spatial resolution. The automated specimen analysis can be described by a two step procedure: single cell classification and evaluation of cell population. For the single cell classifier only features derived from the nucleus are used. The pattern recognition procedures are based on a processor-oriented strategy, and can be adapted to other cytological specimen. The algorithms have been tested with 3 . 10(5) cell images of about 300 specimens.</p>","PeriodicalId":76159,"journal":{"name":"Microscopica acta. Supplement","volume":"6 ","pages":"121-33"},"PeriodicalIF":0.0000,"publicationDate":"1983-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"[Early cancer diagnosis through automated cytoanalysis (Fazytan system)].\",\"authors\":\"E R Reinhardt, R Erhardt\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>A prescreening system for the early detection of uterine cancer was developed. For the diagnosis of each input specimen (PAP-stained), a figure of malignancy has to be calculated automatically. Methods, problems and results of the system are summarized in this paper. Some thousand microscopic subfields of a specimen are successively scanned by an optimized TV-camera with high spatial resolution. The automated specimen analysis can be described by a two step procedure: single cell classification and evaluation of cell population. For the single cell classifier only features derived from the nucleus are used. The pattern recognition procedures are based on a processor-oriented strategy, and can be adapted to other cytological specimen. The algorithms have been tested with 3 . 10(5) cell images of about 300 specimens.</p>\",\"PeriodicalId\":76159,\"journal\":{\"name\":\"Microscopica acta. Supplement\",\"volume\":\"6 \",\"pages\":\"121-33\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1983-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Microscopica acta. Supplement\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Microscopica acta. Supplement","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
[Early cancer diagnosis through automated cytoanalysis (Fazytan system)].
A prescreening system for the early detection of uterine cancer was developed. For the diagnosis of each input specimen (PAP-stained), a figure of malignancy has to be calculated automatically. Methods, problems and results of the system are summarized in this paper. Some thousand microscopic subfields of a specimen are successively scanned by an optimized TV-camera with high spatial resolution. The automated specimen analysis can be described by a two step procedure: single cell classification and evaluation of cell population. For the single cell classifier only features derived from the nucleus are used. The pattern recognition procedures are based on a processor-oriented strategy, and can be adapted to other cytological specimen. The algorithms have been tested with 3 . 10(5) cell images of about 300 specimens.