{"title":"微钙化边界表征。","authors":"Tiago Docusse, Aledir Pereira, Norian Marranghello","doi":"10.1109/MEMB.2009.934583","DOIUrl":null,"url":null,"abstract":"Breast cancer is a disease that can be treated if detected in its early stages. Microcalcifications are high-frequency components on digital images. A transform that deals with frequency components can be used in trying to detect these objects on the breast image. We used the wavelet transform on the proposed work to detect these elements and to classify the nature of their borders, being smooth or rugged.","PeriodicalId":50391,"journal":{"name":"IEEE Engineering in Medicine and Biology Magazine","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/MEMB.2009.934583","citationCount":"8","resultStr":"{\"title\":\"Microcalcification border characterization.\",\"authors\":\"Tiago Docusse, Aledir Pereira, Norian Marranghello\",\"doi\":\"10.1109/MEMB.2009.934583\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Breast cancer is a disease that can be treated if detected in its early stages. Microcalcifications are high-frequency components on digital images. A transform that deals with frequency components can be used in trying to detect these objects on the breast image. We used the wavelet transform on the proposed work to detect these elements and to classify the nature of their borders, being smooth or rugged.\",\"PeriodicalId\":50391,\"journal\":{\"name\":\"IEEE Engineering in Medicine and Biology Magazine\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1109/MEMB.2009.934583\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Engineering in Medicine and Biology Magazine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MEMB.2009.934583\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Engineering in Medicine and Biology Magazine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MEMB.2009.934583","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Breast cancer is a disease that can be treated if detected in its early stages. Microcalcifications are high-frequency components on digital images. A transform that deals with frequency components can be used in trying to detect these objects on the breast image. We used the wavelet transform on the proposed work to detect these elements and to classify the nature of their borders, being smooth or rugged.
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